<<

Review Small- Synthetic Aperture for Continuous Global Biospheric Monitoring: A Review

Sung Wook Paek 1,* , Sivagaminathan Balasubramanian 1, Sangtae Kim 2 and Olivier de Weck 3

1 Samsung SDI Co., Ltd. 130 Samsung-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do 16678, Korea; [email protected] 2 Department of Nuclear Engineering, Hangyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea; [email protected] 3 Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; [email protected] * Correspondence: [email protected]

 Received: 26 June 2020; Accepted: 2 August 2020; Published: 7 August 2020 

Abstract: Space-based radar sensors have transformed observation since their first use by in 1978. Radar instruments are less affected by daylight or weather conditions than optical counterparts, suitable for continually monitoring the global biosphere. The current trends in synthetic aperture radar (SAR) platform design are distinct from traditional approaches in that miniaturized carrying SAR are launched in multiples to form a SAR constellation. A systems engineering perspective is presented in this paper to track the transitioning of space-based SAR platforms from large satellites to small satellites. Technological advances therein are analyzed in terms of subsystem components, standalone satellites, and satellite constellations. The availability of commercial satellite constellations, ground stations, and launch services together enable real-time SAR observations with unprecedented details, which will help reveal the global biomass and their changes owing to anthropogenic drivers. The possible roles of small satellites in global biospheric monitoring and the subsequent research areas are also discussed.

Keywords: synthetic aperture radar; ; biospheric monitoring;

1. Introduction Space-based radar observation has growing potentials for monitoring the global biospheric diversity subject to anthropogenic drivers at geological scales [1]. The performance of radar is less affected by weather and sunlight conditions than that of optical sensors. Satellites with onboard sensors can provide comprehensive coverage of remote areas or vast regions that may be too costly for unmanned aerial vehicles (UAVs) or ground-based platforms, provided that all platforms provide congruent results via calibrations [2–4]. Therefore, it was Seasat, the first satellite dedicated to remote sensing of the Earth’s , that carried the first synthetic aperture radar (SAR) and other radar instruments operable in space. Despite these advantages, miniaturization of radar-carrying satellites was rather slow compared to satellites carrying optical devices due to the lack of commercial-off-the-shelf (COTS) components as well as challenging design requirements for the satellite platform [5,6]. Representative use cases of space-based radar include altimetry, sounding, scatterometry, and so forth in the studies of land, cryosphere, and oceans. Biospheric monitoring is another useful application because radar has high sensitivity in detecting surface changes in a target area and discriminating mobile targets against a background [7]. This paper will consider mainly SAR because of its three-dimensional mapping capability through interferometry. The heritage of Seasat has influenced many of later SAR

Remote Sens. 2020, 12, 2546; doi:10.3390/rs12162546 www.mdpi.com/journal/remotesensing Remote Sens. 2020, 12, 2546 2 of 31 missions for decades, as listed in Table1[ 8–13]; for instance, Shuttle Image Radar (SIR) missions used spare parts of the previous Seasat mission onboard Space Shuttles to test SAR image applications in land use, geology, hydrology, and forestry [14,15]. European Remote-Sensing Satellite (ERS) could obtain radar data in polar regions thanks to its . Two different operational modes were available for SAR of ERS, the imaging mode for high resolution (10m) and the wave mode with 30 m resolution for vector measurement of waves. Figure1 describes the acquisition of imagelets during the wave mode, which may be subdivided into the On-Ground Range Compression (OGRC, 5 km 5 km) × mode and the Onboard Range Compression (OBRC, 5 km 9.6–12 km) mode [16]. The imaging mode, × not shown in Figure1, is identical to the wave mode except that the entire 100 km wide strip is scanned for high-resolution imagery without any movement profile information. This resolution-swath tradeoff is also shown in Advanced Land Observing Satellite (ALOS) whose ScanSAR mode has a coarse 100 m resolution but 250–350 km wide swath. This is 3 to 5 times wider than conventional SAR images and is especially useful for monitoring and rain forest extent with expansive areas of interest [13].

Table 1. Synthetic aperture radar missions (2018).

Resolution Mission Country Duration Band Mass (kg) Swath (km) (m, Az-R) SeaSat USA 1978 L 2290 100 6–25 SIR-A1/B1 USA 1981, 1984 L 2460 50 7–25/6–13 ERS-1/2 Europe 1991–2010 C 2384 100 6–26 1995–2011 2516 100 6–26 ALMAZ-1 USSR 1991–1992 S 3420 280 8–15 JERS-1 1992–1998 L 1400 75 18–18 SIR-C/X Multi 1 1994 C,L/X 11,000 90 7.5–13/6–10 -1 1995–2013 C 3400 500 8–8 SRTM1 Multi 2 2000 C,X 13,600 100 15–8/8–19 Europe 2002–2012 C 8210 100 6–9 (SM) 3 405 80–8 (SC) 3 ALOS Japan 2006–2011 L 3850 70 10–10 (high) 30 10–30 (polar) 350 100–100 (SC) SAR-Lupe 2006– X 770 4 -- RADARSAT-2 Canada 2007–2020 C 2200 18 0.8–1.6 (SL) 5 100 8–9 (std) 500 70–70 (SC) Cosmo- 2007– X 1700 10 1–1 (SL) SkyMed 40 3–3 (SM) 200 30–30 (SC) TerraSAR-X Germany 2007–2020 6 X 1230 10 1–1 (SL) 30 3–1 (SM) 270 40–2 (SC) TecSAR 2008– X 260 4 -- TanDEM-X Germany 2009–2020 6 X 1230 - Same as TSX RISAT-1 2012–2017 C 1860 10 1–1 25 3–4 220 48–8 HJ-1C 2012–2016 S 890 100 5–20 KOMPSat-5 S. Korea 2013–2020 6 X 1400 18 1–1 (high) 30 3–3 (std) 100 5–5 (wide) Sentinel 1A/B Europe 2014– C 2300 80 4–2 (SM) 2016– 400 43–8 (TS) 7 ALOS 2 Japan 2014–2020 6 L 2120 25 1–3 (SL) 70 5–9 (SM) 490 60–45 (SC) 2015– X 1230 10 1–1 (SL) 30 3–1 (SM) 100 20–20 (SC) RCM Canada 2017– C 1430 20 1–1 (SL) 30 3–10 (SM) 500 40–40 (SC) SAOCOM 2018– L 3000 30 10 (Az, SM) 350 100 (Az, TS) 1 C/L-band: USA, X-band: Germany, Italy; 2 C-band: USA, X-band: Germany; 3 SM: stripmap, SC: ScanSAR; 4 Dry mass; 5 SL: spotlight; 6 World Meteorological Organization (WMO) database; 7 TS: TopSAR. Remote Sens. 2020, 12, x FOR PEER REVIEW 3 of 31

ALOS 2 Japan 2014–2020 6 L 2120 25 1–3 (SL) 70 5–9 (SM) 490 60–45 (SC) PAZ Spain 2015– X 1230 10 1–1 (SL) 30 3–1 (SM) 100 20–20 (SC) RCM Canada 2017– C 1430 20 1–1 (SL) 30 3–10 (SM) 500 40–40 (SC) SAOCOM Argentina 2018– L 3000 30 10 (Az, SM) 350 100 (Az, TS) Remote Sens. 2020, 12, 2546 3 of 31 1 C/L-band: USA, X-band: Germany, Italy; 2 C-band: USA, X-band: Germany; 3 SM: stripmap, SC: ScanSAR; 4 Dry mass; 5 SL: spotlight; 6 World Meteorological Organization (WMO) database; 7 TS: TopSAR.

Figure 1.FigureSchematic 1. Schematic view ofview synthetic of synthetic aperture aperture radar rada (SAR)r (SAR) onboard onboard European European Remote-Sensing Remote-Sensing Satellite (ERS): (leftSatellite) SAR (ERS): Wave (left Mode.) SAR Wave (right Mode.) Switching (right) betweenSwitching SARbetween Wave SAR mode Wave and mode SAR and Image SAR Image mode along mode along with their ground swaths. Source: ESA. with their ground swaths. Source: ESA. An important application of SAR is interferometric synthetic aperture radar (InSAR), which was Anfirst important attempted application by time-series of analys SARis is of interferometric Seasat data. The phase synthetic difference aperture in two radar or more (InSAR), SAR images which was first attemptedis measured by time-seriesto yield centimeter- analysis or millimeter-leve of Seasat data.l surface The phase changes difference over large in areas two (squares or more of SAR km) images is measuredat meter-level to yield resolutions, centimeter- making or millimeter-level InSAR ideal for surfacemonitoring changes surface overdeformations large areas of Earth (squares [17]. of km) at meter-levelThe SAR resolutions, images capturing making the same InSAR scene ideal may for be monitoringacquired at two surface different deformations times and/or at of two Earth [17]. The SARslightly images different capturing locations. the The same technique scene has may matu bered acquired since ERS atin the two 1990 differents when the times stabilization and/or at two of satellite orbits allowed for exploiting repeat-ground tracks to visit target areas on a regular basis slightly different locations. The technique has matured since ERS in the 1990s when the stabilization of [18]. Japanese Earth Resources Satellite 1 (JERS-1) also demonstrated two-pass (repeat-pass) cross- satellitetrack orbits interferometry, allowed for exploitingmeaning that repeat-ground different radar tracksimages to are visit obtained target from areas different on a regular orbits basisat [18]. Japanesedifferent Earth Resourcesmoments [19]. Satellite It was 1 the (JERS-1) US-Germany also demonstrated joint mission two-passin 2000, called (repeat-pass) Shuttle Radar cross-track interferometry,Topography meaning Mission that(SRTM), different which performed radar images single-pas ares obtained interferometry from using different one radar orbits antenna at different momentsonboard [19]. Ita wasSpace the Shuttle US-Germany and another joint mounted mission on the in 2000,end of called 60-m mast Shuttle connected Radar to Topography it [20]. As its Mission name suggests, SRTM was a continuation of the SIR mission in 1994 with a two-antenna configuration. (SRTM), which performed single-pass interferometry using one radar antenna onboard a This two-antenna SAR concept is further being developed by German twin-satellite missions as and anothertechnologies mounted for onclose-formation the end of 60-m flight mast have connected become reliable to it [ 20[21].]. As These its name missions suggests, have new SRTM was a continuationobservation of themodes SIR such mission as along-track in 1994 InSAR with aand two-antenna SAR polarimetry configuration. [22]. This two-antenna SAR concept is furtherTraditional being research developed interests by German utilizing twin-satellite SAR data focused missions on asgeosphere, technologies hydrosphere, for close-formation and flight havecryosphere become among reliable different [21 ].realms These (“-spheres”) missions of have Earth newscience observation [23–25]. Note modes that the suchatmosphere as along-track is InSAR andnot included SAR polarimetry in Table 2 because [22]. the purpose of radar observation is to minimize the weather influence on its data; ocean , for example, is covered by hydrosphere in the context of its surface Traditional research interests utilizing SAR data focused on geosphere, hydrosphere, and cryosphere interactions. Biospheric monitoring herein involves efforts to apply SAR data to agriculture, forestry, among diandfferent the studies realms of (“-spheres”)grasslands and of wetlands Earth science [26,27].[ 23When–25 ].it comes Note thatto the the interactions atmosphere between is not the included in Tablebiosphere2 because and the the anthroposphere, purpose of radar SAR observationdata could benefit is tourban minimize management, the weatherresource exploration, influence on its data; oceanbiomass wind, monitoring, for example, vulnerability is covered studies by (e.g., hydrosphere diseases) to name in the a few context as will of be its seen surface in Section interactions. 4 Biospheric[28–32]. monitoring The vulnerability herein involves studies may efforts also toinvolv applye interactions SAR data between to agriculture, anthroposphere forestry, and and other the studies of grasslands and wetlands [26,27]. When it comes to the interactions between the biosphere and the anthroposphere, SAR data could benefit urban management, resource exploration, biomass monitoring, vulnerability studies (e.g., diseases) to name a few as will be seen in Section4[ 28–32]. The vulnerability studies may also involve interactions between anthroposphere and other realms such as geological events leading to disasters, which again affect biosphere [33]. This trend testifies the newly increasing importance of biospheric monitoring for the already mature field of SAR-based Earth remote sensing.

Table 2. Areas of research utilizing SAR data. Source: German Aerospace Center (DLR) [25].

Category Application Temporal Scale Days Weeks Months Years Biosphere Deforestation or fire O O O Biodiversity O O O Cryosphere Sea ice O O Ice cap and glaciers O O Geosphere Volcanic activities O O Seismic activities O O O O Landslides O O Hydrosphere Floods and soil moisture O O Ocean currents and tides OO Remote Sens. 2020, 12, x FOR PEER REVIEW 4 of 31 realms such as geological events leading to disasters, which again affect biosphere [33]. This trend testifies the newly increasing importance of biospheric monitoring for the already mature field of SAR-based Earth remote sensing.

Table 2. Areas of research utilizing SAR data. Source: German Aerospace Center (DLR) [25].

Category Application Temporal Scale Days Weeks Months Years Biosphere Deforestation or fire O O O Biodiversity O O O Cryosphere Sea ice O O Ice cap and glaciers O O Geosphere Volcanic activities O O Seismic activities O O O O Landslides O O Hydrosphere Floods and soil moisture O O Ocean currents and tides O O

Hitherto, spaceborne SAR instruments have been flown onboard monolithic satellites whose mass is a fewRemote tons. Sens. 2020 On, 12 the, 2546 other side of monolith satellites is the category of small satellites.4 of 31 A small satellite (“Smallsat”) weighs less than 500 kg and may be called by other names according to its mass, as listed in FigureHitherto, 2 [34,35]. spaceborne Small SAR satellites instruments have have been become flown onboardan active monolithic area of satellites research whose as mass the CubeSat platform wasis a fewstandardized tons. On the other by sideCalifornia of monolith Polytech satellitesnic is the State category University of small satellites. and Stanford A small satellite University in 1999 [36]. The(“Smallsat”) CubeSat weighs platform less than consists 500 kg and of may multiple be called units by other (“U” names s), according which is to itsa 10 mass, × 10 as listed× 10 cm cubit volume andin is Figure therefore2[ 34,35 ].also Small called satellites “U-class” have become . an active In area terms of research of mass, as the a CubeSat1 to 3U platformCubeSat weighs was standardized by California Polytechnic State University and Stanford University in 1999 [36]. between 1~4The kg, CubeSat falling platform into consiststhe nanosatellite of multiple units regime (“U” s), in which Figure is a 10 2 [37].10 10Although cm cubit volume some andof isthe optical × × sensors havetherefore reached also calledthe extent “U-class” of spacecraft.miniaturization In terms ofas mass, well a as 1 to commercialization 3U CubeSat weighs between to fit 1~4into kg, a 3U class (e.g., Planet)falling that into has the a nanosatellitesize of a shoebox, regime in Figure of2[ 37the]. Althoughadvanced some sensors of the optical featuring sensors multiple have reached bandwidths require largerthe extent volumes, of miniaturization i.e., 6U asor wellmore as commercialization [38,39]. Due to to fitits into lower a 3U classoperational (e.g., Planet) frequency that has a (longer size of a shoebox, most of the advanced sensors featuring multiple bandwidths require larger volumes, wavelength),i.e., a 6U radar or more antenna [38,39]. should Due to its be lower larger operational than satellite frequency payloads (longer wavelength), that operate a radar in visible, antenna , or microwaveshould spectrums. be larger than The satellite radar payloads system that also operate requires in visible, higher infrared, power or throughputs spectrums. than optical payloads becauseThe radar they system must also requirestransmit higher electromagneti power throughputsc pulses than first optical to payloadsthe grou becausend before they mustreceiving the backscatteredtransmit echoes electromagnetic [8,40]. Despite pulses these first to challenges the ground before and constraints, receiving the backscattered there are several echoes [mission8,40]. plans Despite these challenges and constraints, there are several mission plans and startup initiatives for Earth and startupobservation initiatives missions for Earth with observation SAR-equipped missions small satellites, with which SAR-equipped are driven by small the aforementioned satellites, which are driven by scientificthe aforementioned needs as well as performance-costscientific needs advantages as well ofas Smallsat performance-cost constellations [41advantages,42]. Biospheric of Smallsat constellationsmonitoring [41,42]. is moreBiospheric explicitly monitoring manifested as ais scientific more explicitly objective of largemanifested SAR satellites, as a andscientific the same objective is of large SAR expectedsatellites, in Smallsatand the constellations same is expected as well [26 in,43 Smallsat,44]. constellations as well [26,43,44].

Figure 2. Classification of small satellites. The nanosatellite example shows a 3U CubeSat platform. Figure 2. ClassificationSource: NASA, of National small Centresatellites. for Space The Studiesnanosatellite (CNES), Universitatexample shows Politècnica a 3U de CubeSat Catalunya, platform. Source: NASA,KTH RoyalNational Institute Centre of Technology, for SpaceÉcole Studies polytechnique (CNES), féd Universitatérale de Lausanne, Politècnica MIT [34]. de Catalunya, KTH Royal InstituteThe organizationof Technology, of this École paper polytechnique is as follows: Section fédérale2 briefly de Lausanne, introduces MIT SAR [34]. design principles. Section3 investigates current or planned small satellite missions, paying extra attention to their operational details and constellation design if applicable. In addition to minisatellite- and microsatellite- SAR, some larger SAR spacecraft and Cubesat-level non-SAR nanosatellites are also considered. Section4 concludes with potential use cases of small-satellite SAR in global biospheric monitoring as an extension of larger SAR missions. Remote Sens. 2020, 12, 2546 5 of 31

2. Design Principles of Synthetic Aperture Radar The underlying physics is identical between large-satellite SAR and small-satellite SAR in their design process, but the optimization goals might be different. Design principles of Smallsat SAR are unconventional in that minimizing the antenna sizes and the number of observation modes has priority over improving the ground resolution, whose trend is prominent under the launch mass of 200 kg [45]. In general, the best possible ground resolution for stripmap SAR in the along-track (azimuthal) dimension is given by: δx La/2 (1) ≥ where La is the along-track (azimuthal) physical length of the SAR antenna, which is illustrated in Figure3 (left). To avoid ambiguity and maximize the swath, the minimum antenna area that is the product of La and the across-track (cross-track) width Wa should be:

4VλR A = W L > m tan η (2) a a a c

where V is the satellite speed (~7 km/s), λ is the radar wavelength, c is the speed of light, Rm is the range to the middle of the swath, and η is the look angle. The corresponding swath is

c cLa Wg max = = (3) , 2PRF sin η 4V sin η min· under the condition that the ground swath must be wider than the antenna footprint on the ground at the minimum pulse repetition frequency (PRF) equal to 2V/L or the Doppler bandwidth [46]. From the linear relation between the ground swath and the antenna size, it is possible to reduce the antenna length without sacrificing the ground resolution by accepting a smaller swath, or vice versa. The antenna width may also be reduced with a smaller noise bandwidth. The following expression Remoteshows, Sens. however, 2020, 12, thatx FOR reducing PEER REVIEW the antenna width (Wa) has squaring impacts that must be absorbed6 of by31 the noise bandwidth (Bn), the transmit pulse duration (τp), the peak transmission power (Pt), or the numberantenna lengthof observation in order tomodes keep theand signal-to-noise the number of ratio channels (SNR) constant:to cope with their inherent design constraints. While smaller and more efficient commercial-off-the-shelf (COTS) parts are becoming 2 available with respect to communications and powerPtL electronics,aWa τp even more innovative technologies SNRmax (4) such as inter-satellite links (e.g., optical laser communications)∝ Bn or wireless power transfers may be envisioned.

Figure 3. Basics of spaceborne SAR: (left) Nomenclature of design parameters. (right) Ground-range Figure 3. Basics of spaceborne SAR: (left) Nomenclature of design parameters. (right) Ground-range resolution as a function of look angle (ground swath) and bandwidth. Source: JPL, . resolution as a function of look angle (ground swath) and bandwidth. Source: JPL, Capella Space. The ground-range resolution is dependent on the chirp bandwidth as well as the incidence angle: 3. Synthetic Aperture Radar Satellite Missions c This section surveys spaceborne SAR missionsδgr = flown already or being planned. First, earlier SAR(5) 2B sin η missions featuring satellite constellations or formation flight are covered in Section 3.1.

3.1. Medium/Large Satellite Constellations SAR missions in Table 1 have satellite launch mass greater than 500 kg and do not technically fall into the small satellite category. Either medium (500 kg to 1 ton) or large (>1 ton), these satellites were designed following rather conventional principles, less affected by design constraints in mass and volume than small satellites. Nonetheless, deployment and operation details of missions in Table 1 still provide useful guidelines. For example, SAR-Lupe is a 5-satellite system and Cosmo-SkyMed is a 4-satellite system, being the largest and the second-largest (homogeneous) constellations launched so far. Future missions with larger numbers of small satellites would require efficient strategies for constellation design and deployment, for which SAR-Lupe and Cosmo-SkyMed could be good references. TanDEM-X demonstrates various formation flight technologies with two satellites flying close to each other in space, and HJ-1C is an interesting example of a heterogeneous constellation of SAR platforms and optical platforms.

3.1.1. SAR-Lupe SAR-Lupe is Germany’s first satellite system for global surveillance, delivering radar images for the German Armed Forces for at least ten years since its launch. The spacecraft design by the OHB-System AG utilized a parabolic reflector antenna instead of active beam-steering antennas, which led to major savings in the cost of instrument development [47,48]. However, the size of a reflector antenna (3.3 m × 2.7 m) poses a major volume constraint during satellite stowage and launch phases as shown in Figure 4, necessitating a dedicated launch for each satellite. The five identical SAR satellites were launched between 2006 and 2008, with individual launches separated by 4 to 8 months [49]. The five satellites are distributed in three orbital planes, marked with plane numbers and corresponding satellites in Figure 4 (right). Orbital planes 1 and 2 are separated by 64° in longitude, and orbital planes 2 and 3 are separated by 65°. Satellite-pairs in orbital planes 1 and 3 have phase angles differing by 69°. Together with a near-polar inclination (98.2°), this satellite arrangement provides the SAR-Lupe constellation with both global coverage and short response time.

Remote Sens. 2020, 12, 2546 6 of 31 where by better ground-range resolution would increase the bandwidth and thus require a higher transmitter power per Equation (4). Unlike 2-D optical images, this altimetry capability of SAR leads to numerous 3-D applications, which is why the ground-range resolution is an important performance metric; the design specifications of an optical satellite only mention ground sample distance (GSD) whereas SAR satellites are usually specified by both azimuthal resolution and ground-range resolution as listed in Table1. Figure3 (right) describes the multi-parametric dependence of ground-range resolution on look angle and bandwidth. The data rate should also be carefully chosen to maximize on-time of SAR and the transferrable data volume, under the ground station constraints, in addition to the relationship among the antenna size, the orbit geometry, the SNR, and the power requirement. Small satellites usually minimize the number of observation modes and the number of channels to cope with their inherent design constraints. While smaller and more efficient commercial-off-the-shelf (COTS) parts are becoming available with respect to communications and power electronics, even more innovative technologies such as inter-satellite links (e.g., optical laser communications) or wireless power transfers may be envisioned.

3. Synthetic Aperture Radar Satellite Missions This section surveys spaceborne SAR missions flown already or being planned. First, earlier SAR missions featuring satellite constellations or formation flight are covered in Section 3.1.

3.1. Medium/Large Satellite Constellations SAR missions in Table1 have satellite launch mass greater than 500 kg and do not technically fall into the small satellite category. Either medium (500 kg to 1 ton) or large (>1 ton), these satellites were designed following rather conventional principles, less affected by design constraints in mass and volume than small satellites. Nonetheless, deployment and operation details of missions in Table1 still provide useful guidelines. For example, SAR-Lupe is a 5-satellite system and Cosmo-SkyMed is a 4-satellite system, being the largest and the second-largest (homogeneous) constellations launched so far. Future missions with larger numbers of small satellites would require efficient strategies for constellation design and deployment, for which SAR-Lupe and Cosmo-SkyMed could be good references. TanDEM-X demonstrates various formation flight technologies with two satellites flying close to each other in space, and HJ-1C is an interesting example of a heterogeneous constellation of SAR platforms and optical platforms.

3.1.1. SAR-Lupe SAR-Lupe is Germany’s first military satellite system for global surveillance, delivering radar images for the German Armed Forces for at least ten years since its launch. The spacecraft design by the OHB-System AG utilized a parabolic reflector antenna instead of active beam-steering antennas, which led to major savings in the cost of instrument development [47,48]. However, the size of a reflector antenna (3.3 m 2.7 m) poses a major volume constraint during satellite stowage and launch × phases as shown in Figure4, necessitating a dedicated launch for each satellite. The five identical SAR satellites were launched between 2006 and 2008, with individual launches separated by 4 to 8 months [49]. The five satellites are distributed in three orbital planes, marked with plane numbers and corresponding satellites in Figure4 (right). Orbital planes 1 and 2 are separated by 64 ◦ in longitude, and orbital planes 2 and 3 are separated by 65◦. Satellite-pairs in orbital planes 1 and 3 have phase angles differing by 69◦. Together with a near-polar inclination (98.2◦), this satellite arrangement provides the SAR-Lupe constellation with both global coverage and short response time. Remote Sens. 2020,, 1212,, 2546x FOR PEER REVIEW 7 of 31 Remote Sens. 2020, 12, x FOR PEER REVIEW 7 of 31

Figure 4. Launch and deployment of SAR-Lupe spacecraft: (left) Miniature models of SAR-Lupe and Figurethe launch 4. and upper deployment stage. (middle of SAR-Lupe ) Artist’s spacecraft: concept of (SAR-Lupeleft) Miniature in space. models (right of ) SAR-Lupe Illustration and of theSAR-Lupe launch vehicleconstellation. upperupper Source: stage.stage. ( middleOHB-System) Artist’s AG. concept ofof SAR-Lupe inin space.space. (right) Illustration of SAR-Lupe constellation. Source: OHB-System AG. Observation of SAR-Lupe is made in the X band with a frequency of 9.65 GHz and a wavelength of 3.1Observation cm, capable of ofof SAR-Lupe SAR-Lupechange detection is is made made based in in the the on X X band SARband withinterferometry with a a frequency frequency [50]. of of 9.65 The 9.65 GHz stripmap GHz and and a (60 wavelengtha wavelength km × 8 km) of 3.1 cm, capable of change detection based on SAR interferometry [50]. The stripmap (60 km 8 km) observationof 3.1 cm, capable of SAR-Lupe of change provides detection nadir-looking based on SAR scenes, interferometry whereas [50]. the Thespotlight stripmap (5.5 (60km km × 5.5 ×× 8 km) observation of SAR-Lupe provides nadir-looking scenes, whereas the spotlight (5.5 km 5.5 km) scenesobservation require of theSAR-Lupe orienting provides of a spacecraft nadir-looking towards scenes, a target whereas area to thincreasee spotlight integration (5.5 km time × 5.5 for km) 0.5 scenesm resolution. requirerequire When thethe orientingorienting the image ofof a acquisitiona spacecraft spacecraft is towards towards complete a a target , targetthe spacecraft area area to to increase increase returns integration tointegration its standby time time mode for for 0.5 for0.5 m resolution.rechargingm resolution. two When When 66 theAh the imagelithium-ion image acquisition acquisition batteries is is complete,with complete solar the,panels. the spacecraft spacecraft Amongst returns returns L, S, C, toto itsandits standbystandby X bands modemode listed for in rechargingFigure 5 used two for 66 radarAh Ah lithium-ion lithium-ion sensors, the batteries batteries X band with with requ sola solariresr panels.the panels. smallest Amongst Amongst antenna L, L, S, S,size,C, C, and andwhich X bands X bandsenabled listed listed the in inFigureadoption Figure 5 5 usedof used a parabolicfor for radar radar antennasensors, sensors, whosethe the X X band bandsize wouldrequ requiresires be the theunacceptable smallest antenna in other size,size, spectral whichwhich bands enabledenabled [51]. thethe It adoptionalso led to ofof a acompacta parabolicparabolic design antenna antenna of power whose whose systems size size would would such be asbe unacceptable solar unacceptable arrays inproviding otherin other spectral 550 spectral W bands at thebands [ 51end]. [51]. Itof also life It led(EOL),also to led a an compactto ordera compact designof magnitude design of power of smallerpower systems systems than such the assuch 7 solar kW as arrayspowersolar arrays providinggeneration providing 550 (EOL) W 550 at by the W ALOS endat the of in end life Table (EOL),of life 1. anWhen(EOL), order itan ofcomes order magnitude ofto magnitudeonboard smaller batteries, smaller than the thanALOS 7 kW the powerused 7 kW nickel-cadmium generation power generation (EOL) batteries by (EOL) ALOS andby in ALOS TableSAR-Lupe 1in. WhenTable used it1. comeslithium-ionWhen toit comes onboard for the to batteries,firstonboard time in ALOSbatteries, SAR usedsatellites. ALOS nickel-cadmium Althoughused nickel-cadmium lithium-ion batteries andbatteries batteries SAR-Lupe do and not used haveSAR-Lupe lithium-iona “memory used foreffect”lithium-ion the suffered first for time the by in firstnickel-cadmium SAR time satellites. in SAR satellites.batteries, Although Althoughthey lithium-ion only lithium-ionbecame batteries available batteries do not after have do more not a “memoryhave lenient a “memory electric- effect” supowereffect”ffered sufferedrequirements by nickel-cadmium by nickel-cadmium owing batteries,to their batteries, higher they only costs.they became on Afterly became availableall, SAR-Lupe available after more afteris an lenient moreinteresting lenient electric-power example electric- requirementsfeaturingpower requirements efficient owing onboard toowing their power to higher their management costs. higher After costs. at all, a Afterspacecraft SAR-Lupe all, SAR-Lupe level is an and interesting ais constellation an interesting example architecture featuringexample ewithfeaturingfficient multiple onboard efficient orbital power onboard planes management power at a higher management at a spacecraftlevel, both at a level ofspacecraft which and a inspired constellation level and later a architectureconstellation SAR constellations with architecture multiple with orbitalsmallwith multiple satellites. planes atorbital a higher planes level, at botha higher of which level, inspired both of laterwhich SAR inspired constellations later SAR with constellations small satellites. with small satellites.

Figure 5. Nomenclature of electromagnetic spectra per the IEEE and International Telecommunication UnionFigure (ITU)5. standards.Nomenclature P-band, of whichelectromagnetic will be used forspec thetra European per the BIOMASS IEEE satellite,and International is defined as theFigureTelecommunication interval 5. 420–450Nomenclature MHzUnion beyond (ITU) of standards. theelectromagnetic L band. P-band, As the frequencyspecwhichtra will per increases be usedthe (wavelengthforIEEE the Europeanand decreases)International BIOMASS from leftTelecommunicationsatellite, to right, is defined the antenna asUnion the size (ITU)interval decreases standards. 420–450 while P-band,MHz the throughput beyond which thewill and Lbe band. the used susceptibility forAs the Europeanfrequency to rain BIOMASS increases.increases Source:(wavelengthsatellite, KTH is defined decreases) [51]. as the from interval left to 420–450right, the MHz antenna beyond size thedecreases L band. while As the frequencythroughput increases and the susceptibility(wavelength decreases) to rain increases. from left Source: to right, KTH the [51]. an tenna size decreases while the throughput and the 3.1.2.susceptibility Cosmo-SkyMed to rain increases. Source: KTH [51]. 3.1.2. Cosmo-SkyMed COSMO-SkyMed is the acronym for Constellation of Small Satellites for Mediterranean Basin 3.1.2. Cosmo-SkyMed Observation,COSMO-SkyMed conceived is by the the acronym Italian Space for Agency.Constellation Funded of bySmall the ItalianSatellites Ministry for Mediterranean of Research and Basin the ItalianObservation,COSMO-SkyMed Ministry conceived of Defense, is by the thethe acronym satelliteItalian Space systemfor Constellation Agency. has dual-use Funded of (civilian Small by the Satellites and Italian military) Mifornistry Mediterranean applications of Research ranging Basin and theObservation, Italian Ministry conceived of Defense, by the Italian the satellite Space Agency.system has Funded dual-use by the (civilian Italian and Ministry military) of Research applications and the Italian Ministry of Defense, the satellite system has dual-use (civilian and military) applications

Remote Sens. 2020, 12, 2546 8 of 31

Remote Sens. 2020, 12, x FOR PEER REVIEW 8 of 31 from reconnaissance and risk management to the monitoring of biospheres such as marine/coastal environments,ranging from reconnaissance agriculture, and and forestry. risk management Because the launchto the datesmonito ofring the firstof biospheres satellite (June such 2007) as andmarine/coasta the last satellitel environments, (November agriculture, 2010) are a morend forest thanry. three Because years the apart, launch the dates constellation of the first size satellite grew rather(June 2007) gradually, and the operating last satellite with (Nov intermediateember 2010) configurations. are more than In three each phase,years apart, all satellites the constellation are in the samesize grew orbital ra plane;ther gradually,the inter-satellite operating angle with decreased intermediate from 180 ◦ configurations.in two-satellite Inconfiguration each phase, to 90 all◦ insatellites a four-satellite configuration in Figure6. The coverage performance during each stage is listed in Tables3 and4 ; the mean revisit time of 3 to 6 h at the full-blown state is still longer than three-plane SAR-Lupe whose revisit time is expected to be about an hour [52,53].

Figure 6.6.Deployment Deployment steps steps of the of COSMO-SkyMed the COSMO-SkyMed (Constellation (Constellation of Small Satellites of Small for MediterraneanSatellites for BasinMediterranean Observation) Basin configuration. Observation) configuration.

Table 3. Revisit time of Cosmo-SkyMed during constellation deployment. Table 3. Revisit time of Cosmo-SkyMed during constellation deployment. Configuration Average Revisit Time, h Worst Revisit Time, h Configuration Average Revisit Time, h Worst Revisit Time, h # Satellites# Satellites Left Left and and Right Right Right Right Left Left and and Right Right Right Right 1 1 18 to 18 35 to1 35(12 1 (12 to 23) to 23)2 23737 to 64to 64 (25 (25 to 44)to 44) 156 156 (60) (60) 252 252 (120)(120) 22 9 to9 18to (618 to(6 12)to 12) 19 19to 35to 35 (13 (13 to 24)to 24) 60 60 (36) (36) 108 108 (60)(60) 33 6 to6 12to (412 to(4 8)to 8) 13 13to 24to 24 (9 to(9 16)to 16) 36 36 (36) (36) 60 60 (36)(36) 44 5 to5 9to (3 9 to(3 6)to 6) 10 10to 18to 18 (6 to(6 12)to 12) 24 24 (12) (12) 60 60 (24)(24) 11 Nominal;Nominal; 22 Extended.Extended.

Table 4. Areal coverage response of Cosmo-SkyMed during constellation deployment.

ConfigurationConfiguration Coverage Coverage After After 12 12 h, %h, % Coverage Coverage After After 24 24 h, h, % % # Satellites# Satellites Left Leftand Rightand Right Right Right Left Left and and Right Right Right Right 1 - - 67 (85) 38 (55) 1 - - 67 (85) 38 (55) 2 62 1 (84) 2 41 (62) 81 (92) 64 (84) 2 62 1 (84) 2 41 (62) 81 (92) 64 (84) 3 88 (98) 62 (84) 96 (99.97) 84 (98) 3 88 (98) 62 (84) 96 (99.97) 84 (98) 44 97 (100) 97 (100) 80 80 (99) (99) 100 100 (100) (100) 95 95 (100) (100) 1 Nominal; 2 Extended. 1 Nominal; 2 Extended. However, the all-in-one-plane architecture of COSMO-SkyMed enables easy transition of its orbitalHowever, configuration the all-in-one-plane from the nominal architecture mode to se ofveral COSMO-SkyMed interferometric modes, enables namely easy transition “tandem” of and its orbital“tandem-like configuration (one-day from interferometry)” the nominal mode [54]. toFirst, several in tandem interferometric interferometry, modes, namelytwo satellites “tandem” are andseparated “tandem-like in two orbit (one-day planes interferometry)” slightly differing [ 54in]. the First, ascending in tandem nodes interferometry, by 0.08°, denoted two as satellites AN (blue) are separatedin Figure 6, in to two guarantee orbit planes exactly slightly overlapping differing ground in the ascendingtracks. If the nodes satellites by 0.08 are◦, denotedin a single as orbit, AN (blue) they inwill Figure have6 ,slightly to guarantee different exactly grou overlappingnd tracks due ground to orbi tracks.tal regression, If the satellites which areis called in a single J2 (Earth’s orbit, theyoblateness) will have effects slightly [55]. The different phasing ground of the tracks two satellites due to orbitalis also adjusted regression, such which that the is called resulting J2 (Earth’s leader- oblateness)follower pair e ffachievesects [55 ].identical The phasing incidence of theangles. two In satellites other words, is also the adjusted two satellites such that acquire the resultingimagery leader-followerof the same scenes pair achieveswith the identicalsame geometry, incidence with angles. a delay In other of 20 words, s. Second, the two in satellitesthe tandem-like acquire imageryconfiguration, of the two same satellites scenes withstay theon the same same geometry, orbit plane with at a delaya distance of 20 of s. 67.5°. Second, This in specific the tandem-like angle is configuration,used instead of two90° for satellites the tandem-like stay on the configuration same orbit plane to achieve at a distance “one-day of interferometry” 67.5◦. This specific with angle 237/16 is usedrepeat instead cycles; of a 90satellite◦ for the in tandem-likethis orbit completes configuration 14 and to 13/16 achieve revolutions “one-day after interferometry” 16 days (denominator), with 237/16 repeatand the cycles; remaining a satellite 3/16 revolution in this orbit to completes complete 14an andinteger 13/16 number revolutions corresponds after 16 to days 67.5° (denominator), (=3/16 × 360). andThe thetwo remainingsatellites with 3/16 this revolution phase spacing to complete visit anthe integer same ground number target corresponds with an to exact 67.5 ◦1-day(=3/16 interval,360). × Theas illustrated two satellites by COSMO-2 with this phaseand COSMO-3 spacing visit in Figure the same 7 (right). ground The target orbit with is a ansun-synchronous exact 1-day interval, orbit with an inclination of 97.86°, a nominal altitude of 620 km, and the local time of the ascending node (LTAN) at 6:00 (/dust orbit). Remote Sens. 2020, 12, 2546 9 of 31 as illustrated by COSMO-2 and COSMO-3 in Figure7 (right). The orbit is a sun-synchronous orbit withRemote an Sens. inclination 2020, 12, x FOR of 97.86 PEER◦ REVIEW, a nominal altitude of 620 km, and the local time of the ascending9 of node 31 (LTAN)Remote atSens. 6:00 2020 (dawn, 12, x FOR/dust PEER orbit). REVIEW 9 of 31

Figure 7. Orbital configuration of the COSMO-SkyMed constellation: (left) Tandem configuration. FigureFigure 7. 7.Orbital Orbital configuration configuration of of the the COSMO-SkyMed COSMO-SkyMed constellation: (left (left) )Tandem Tandem configuration. configuration. (right) Tandem-like configuration. Source: ASI. (right(right) Tandem-like) Tandem-like configuration. configuration. Source: Source: ASI. ASI. The radar transmitter and receiver of each COSMO satellite operate through an electrically TheThe radar radar transmitter transmitter and and receiver receiver of of each each COCOSMOSMO satellitesatellite operateoperate through an electricallyelectrically steerablesteerablesteerable multi-beammulti-beam multi-beam [[56].56 [56].]. This This active active active sensing sensing sensing scheme schemescheme necessitates necessitates aa a COSMOCOSMO COSMO satellite satellite toto to managemanage manage andand and storestorestore its its electricalits electrical electrical power power power more more more effi cientlyefficiently efficiently than than otherthan otherother passive passivepassive SAR systemsSARSAR systemssystems (e.g., SAR-Lupe). (e.g., SAR-Lupe). The nominal TheThe capacitynominalnominal ofcapacity capacity a COSMO of of a COSMOa satellite COSMO issatel satel 336litelite Ah, is is nearly336 336 Ah, Ah, three nearly nearly times three three larger timestimes than largerlarger that than of athat SAR-Lupe ofof aa SAR-LupeSAR-Lupe satellite. Thesatellite.satellite. battery The The cells battery battery constituting cells cells constituting constituting a COSMO a aCOSMO satellite COSMO aresate sate muchllitellite are are smaller much much in smallersmaller size, however, in size, however, with 18-mm-wide, withwith 18- 18- 650-mm-longmm-wide,mm-wide, 650-mm-long 650-mm-long cylindrical cylindrical footprint cylindrical depicted footprint footprint in depicted depicted Figure8 in (left).in FigureFigure A total 88 (left).(left). of 2016 A total lithium-ion of 2016 lithium-ionlithium-ion cylindrical cellscylindricalcylindrical are connected cells cells are are inconnected connected a 9s224p in configuration,in a a9s224p 9s224p configurat configurat meaningion,ion, that meaningmeaning 9 cells thatthat are 99 first cellscells connected are first connectedconnected in series inandin thenseriesseries 224 and and such then then series-strings, 224 224 such such series-strings, series-strings, distributed distribut acrossdistribut eighteded acrossacross modules eighteight in modules Figuremodules8 (right),in Figure are 88 connected (right),(right), areare in parallelconnectedconnected [57 ,in58 inparallel]. parallel This configuration [57,58]. [57,58]. This This configuration provides configuration a maximum provides provides current a a maximum maximum of 650 currentcurrent A (460 Aof for650 the A (460(460 10-s AA maximum forfor the the duration)10-s10-s maximum maximum in Spotlight duration) duration) mode in in Spotlight and Spotlight 450 A mode mode (330 Aand and for 450 450 the A A 10-min (330 (330 AA maximum forfor thethe 10-min10-min duration) maximum in Stripmap duration)duration) mode. inin TheStripmapStripmap power mode. consumption mode. The The power power of a SARconsum consum payloadptionption in of of the a a SAR twoSAR modespayload payload is 13inin kWthethe andtwotwo 7modes kW, respectively. is 13 kW andand The 77 powerkW,kW, subsystemrespectively.respectively. supports The The power power a fully subsystem subsystem polarimetric supports supports SAR a (PolSAR)a fully fully polarimetric polarimetric where only SAR SAR one (PolSAR)(PolSAR) linear polarization where onlyonly oneone is received linear linear atpolarization eachpolarization interrogation is isreceived received [59 at]. at each each interrogation interrogation [59]. [59].

Figure 8. Energy storage of a COSMO satellite: (left) Internal structure of a US18650 hard-carbon FigureFigure 8.8. Energy storage of a COSMO satellite: ( (leftleft) )Internal Internal structure structure of of a aUS18650 US18650 hard-carbon hard-carbon lithium-ion cell. (middle) Battery packs (8) consisting of 2016 identical batteries. (right) SAR-Lupe’s lithium-ionlithium-ion cell.cell. ((middlemiddle)) BatteryBattery packspacks (8)(8) consisting consisting of of 2016 2016 identical identical batteries. batteries. ( right(right)) SAR-Lupe’s SAR-Lupe’s 66 66 Ah battery packs. Source: SONY, ABSL, COM DEV Ltd. [57]. Ah66 Ah battery battery packs. packs. Source: Source: SONY, SONY, ABSL, ABSL, COM COM DEV DEV Ltd. Ltd. [57 [57].]. Both SAR-Lupe and COSMO-SkyMed constellations reserve the capability of their satellites to BothBoth SAR-LupeSAR-Lupe and COSMO-SkyMed constellations constellations reserve reserve the the capability capability of of their their satellites satellites to to reconfigure their orbits. The resulting launch mass or each satellite was a ton or more, however, reconfigurereconfigure their their orbits. orbits. The The resulting resulting launch launch mass mass or eachor each satellite satellite was was a ton a orton more, or more, however, however, electric electric propulsion seems to be an alternative of chemical propulsion for small satellites to achieve propulsionelectric propulsion seems to beseems an alternative to be an alternative of chemical of propulsion chemicalfor propulsion small satellites for small to achieve satellites miniaturization, to achieve miniaturization, as will be discussed later. Still, medium-to-large satellites will continue to provide asminiaturization, will be discussed as later.will be Still, discussed medium-to-large later. Still, satellitesmedium-to-large will continue satellites to provide will continue responsive to provide access to responsive access to observation targets, complementing small-satellite constellations’ wide coverage observationresponsive access targets, tocomplementing observation targets, small-satellite compleme constellations’nting small-satellite wide coverageconstellations’ [52,53 wide]. The coverage COSMO- [52,53]. The COSMO-SkyMed mission demonstrated another way of cost reduction using commercial SkyMed[52,53]. The mission COSMO-SkyMed demonstrated mission another demonstrated way of cost reduction another way using of commercial cost reduction cylindrical using commercial lithium-ion cylindrical lithium-ion batteries for power storage, which can be applied to small satellites as well. batteriescylindrical for lithium-ion power storage, batteries which for can power be applied storage, to which small can satellites be applied as well. to small satellites as well.

Remote Sens. 2020, 12, x FOR PEER REVIEW 10 of 31

Remote Sens. 2020, 12, 2546 10 of 31 3.1.3.Remote TanDEM-X Sens. 2020, 12 , x FOR PEER REVIEW 10 of 31 The TanDEM-X (TDX, 2007) mission is an extension of the TerraSAR-X (TSX, 2010) mission 3.1.3. TanDEM-X flying3.1.3. twoTanDEM-X identical satellites in a close formation to achieve a highly flexible SAR constellation. FollowingTheThe TanDEM-X TanDEM-Xthe previous (TDX, (TDX, mission 2007) 2007) missionname mission (TerraSAR-X), is anis extensionan extension TanDEM-X of the of TerraSAR-Xthe TerraSAR-Xmeans (TSX,“TerraSAR-X (TSX, 2010) 2010) mission add-on mission flying for Digitaltwoflying identical twoElevation identical satellites Measurement,” satellites in a close in formation a bothclose offormatio to whic achievehn wereto a achieve highly implemented flexiblea highly SAR flexiblethrough constellation. SAR a Public-Private- constellation. Following PartnershiptheFollowing previous theof mission theprevious German name mission (TerraSAR-X), Aerospace name center (TerraSAR-X), TanDEM-X (DLR) meansand TanDEM-X European “TerraSAR-X means Aeronautic add-on “TerraSAR-X forDefense Digital add-on and Elevation Space for (EADS)Measurement,”Digital Company Elevation both Astrium Measurement,” of which (now were Airbus implementedboth Defense of whic throughanh dwere Space). aimplemented Public-Private-Partnership The SAR payload through of botha Public-Private- ofTDX the and German TSX AerospacehasPartnership flight heritage center of the (DLR)dating German andback Aerospace European to Shuttle center Aeronauticmissio (DnsLR) such Defense and as SIR-XEuropean and and Space AeronauticSRTM, (EADS) which Defense Company tested andthe Astrium single-Space (nowpass(EADS) SAR Airbus Company interferometry Defense Astrium and (InSAR) Space). (now Airbusin The the SAR XDefense band payload [60]. and of TheSpace). both primary TDX The SAR and objective TSXpayload has of of flightthe both mission heritage TDX andis datingdigital TSX elevationbackhas flight to Shuttle model heritage missions (DEM) dating generation, such back as to SIR-X Shuttle for andwhich missio SRTM, bistaticns such which processing as testedSIR-X and the is employed single-passSRTM, which [61]; SAR tested both interferometry thespacecraft, single- (InSAR)lesspass than SAR in2 km interferometry the apart X band as represented [60 ].(InSAR) The primary in Figurethe X objective band 9 (left), [60]. orient of The the theirprimary mission SAR isobjective instruments digital of elevation the to missiona common model is digital (DEM)target, whichgeneration,elevation provides model for which different (DEM) bistatic generation, viewing processing angles for which is [62]. employed bistatic Both spacecraftprocessing [61]; both spacecraft, simultaneouslyis employed less [61]; thanreceive both 2 km spacecraft, echoes apart asof signalsrepresentedless than transmitted 2 km in Figure apart by 9as (left), onerepresented of orient them, their in which Figure SAR minimi instruments 9 (left),zes orient temporal to their a common SAR decorrelation. instruments target, which The to providesa resultantcommon di target,single-fferent viewingpasswhich interferometry provides angles [62 different]. Bothdoes spacecraft notviewing suffer angles simultaneously accuracy [62]. loss,Both receivewhich spacecraft echoeswould simultaneously ofaffect signals repeat-pass transmitted receive (multi-pass) echoes by one of of interferometrythem,signals which transmitted minimizes with aby single one temporal of satellite. them, decorrelation. which An exampl minimie The zesof resultantbistatictemporal InSAR single-passdecorrelation. is the TanDEM-X interferometry The resultant Forest/Non- does single- not Forestsupassffer accuracyMapinterferometry in which loss, which thedoes global wouldnot rawsuffer aff dataect accuracy repeat-pass set with loss, 50(multi-pass) m which × 50 m would ground interferometry affect independent repeat-pass with pixels a single (multi-pass) were satellite. used Antointerferometry classify example forest of bistatic withand non-foresta InSAR single is satellite. the areas TanDEM-X (urban An exampl settlements Foreste of/Non-Forest bistatic or freshwater), InSAR Map inis whichthe as TanDEM-Xshown the global in Figure Forest/Non- raw data10 [63]. set withTheForest second 50 mMap 50 interferometricin mwhich ground the independentglobal mode raw is data the pixels set pursuit with were 50 usedmonostatic m × to 50 classify m ground mode, forest independentwhose and non-forestTx/Rx pixels operations areas were (urban used are × decoupledsettlementsto classify in orforest two freshwater), satellitesand non-forest as shown areas in (urbanFigure 9settlements10 (r[ight).63]. The The or second amount freshwater), interferometric of temp asoral shown decorrelation mode in Figure is the 10 pursuittherein [63]. ismonostaticThe still secondsmall mode, compared interferometric whose toTx the/Rx repeat-passmode operations is the counterpart. arepursuit decoupled monostatic In inaddition two mode, satellites to the whose asaforementioned shown Tx/Rx in operations Figure multistatic9 (right). are The(bistaticdecoupled amount or in ofmonostatic) two temporal satellites decorrelation baseline, as shown inthe thereinFigure TDX 9 is (r stillmissionight). small The concept comparedamount ofdemonstrated temp to theoral repeat-pass decorrelation the counterpart.along-track therein interferometryInis addition still small to compared the (ATI) aforementioned with to fourthe repeat-pass inter- multistatic or intra-satellite counterpart. (bistatic or phase monostatic)In addition centers. to baseline, Thethe aforementionedATI the technique TDX mission can multistatic be concept used todemonstrated(bistatic resolve theor velocitymonostatic) the along-track of ocean baseline, interferometry currents, the iceTDX drift (ATI) mission, and with other fourconcept on-ground inter- demonstrated or intra-satelliteobjects (e.g., the transportation phase along-track centers. Thetraffic)interferometry ATI [64–66]. technique (ATI) can with be used four to inter- resolve or intra-satellite the velocity of phase ocean centers. currents, The ice ATI drift, technique and other can on-ground be used objectsto resolve (e.g., the transportation velocity of ocean traffi c)currents, [64–66]. ice drift, and other on-ground objects (e.g., transportation traffic) [64–66].

.

Figure 9. Twin-satellite measurement modes of the TanDEM-X/TerraSAR-X mission: (left) Multistatic SARFigure in 9. aTwin-satellite bistatic or monostatic measurement mode modes for of digital the TanDEM-X elevation/TerraSAR-X measurement. mission: (right (left) Along-track) Multistatic Figure 9. Twin-satellite measurement modes of the TanDEM-X/TerraSAR-X mission: (left) Multistatic interferometrySAR in a bistatic for or monostaticobject move modement for detection. digital elevation Source: measurement.DLR. (right) Along-track interferometry SAR in a bistatic or monostatic mode for digital elevation measurement. (right) Along-track for object movement detection. Source: DLR. interferometry for object movement detection. Source: DLR.

Figure 10. Examples of TanDEM-X Forest/Non-Forest map: (left) Germany. (middle) South America over Figure 10. Examples of TanDEM-X Forest/Non-Forest map: (left) Germany. (middle) South America Amazon Rainforest. (right) Amazon Rainforest, State of Rondonia, Brazil (zoomed-in). Source: DLR. overFigure Amazon 10. Examples Rainforest. of TanDEM-X (right) Amazon Forest/Non-Forest Rainforest, State map: of (left Rondonia,) Germany. Brazil (middle (zoomed-in).) South America Source: DLR.Theover TSX Amazon spacecraft Rainforest. retains (right its) sun-synchronousAmazon Rainforest, dawn-dusk State of Rondonia, orbit (LTANBrazil (zoomed-in).= 18:00) with Source: a 515 km altitudeDLR. and a revisit period of 11 days with 167 orbits, or 15 and 2/11 revolutions per day. The TDX orbit uses eccentricity-inclination separation with respect to the TSX orbit, through which the two

Remote Sens. 2020, 12, x FOR PEER REVIEW 11 of 31

RemoteRemoteThe Sens. Sens. TSX2020 2020 ,spacecraft,12 12,, 2546 x FOR PEER retains REVIEW its sun-synchronous dawn-dusk orbit (LTAN = 18:00) with 11a of51511 31 of km 31 altitude and a revisit period of 11 days with 167 orbits, or 15 and 2/11 revolutions per day. The TDX orbit usesThe TSXeccentricity-inclination spacecraft retains its separationsun-synchronous with respectdawn-dusk to the orbit TSX (LTAN orbit, = through18:00) with which a 515 the km two spacecraft leave a helix-shaped trajectory relative to a virtual reference in between. The procedures spacecraftaltitude and leave a revisit a helix-shaped period of 11 trajectory days with relative 167 orbits, to a or virtual 15 and reference 2/11 revolutions in between. per day. The The procedures TDX for eccentricity-inclination separation and the relative trajectory are depicted in Figure 11. First, fororbit eccentricity-inclination uses eccentricity-inclination separation separation and the with relative respect trajectory to the TSX are orbit,depicted through in Figure which 11. the First, two the the ascending node of the TDX orbit plane is shifted by a small offset angle to provide horizontal ascendingspacecraft nodeleave aof helix-shaped the TDX orbit trajectory plane relativeis shifted to a byvirtual a small reference offset in angle between. to provide The procedures horizontal distancing with maximum distance at equator crossings, and the subsequent eccentricity offset provides distancingfor eccentricity-inclination with maximum separation distance andat equator the relative crossings, trajectory and are the depicted subsequent in Figure eccentricity 11. First, the offset vertical (radial) distancing maximized at the poles. Small changes in the argument of perigee may providesascending vertical node of(radial) the TDX distancing orbit plane maximized is shifted at by the a smallpoles. offset Small angle changes to provide in the horizontalargument of alsodistancing be made with to increasemaximum inter-satellite distance at distanceequator incrossings, medium and latitude the subsequent regions. This eccentricity kind of orbitoffset and perigee may also be made to increase inter-satellite distance in medium latitude regions. This kind of itsprovides building vertical procedure (radial) have distancing been proposed maximized for consistent at the poles. separation Small distance,changes in which the argument in turn reduces of orbit and its building procedure have been proposed for consistent separation distance, which in turn collisionperigee hazardsmay also evenlybe made along to increase the orbit inter-satellite [67,68]. distance in medium latitude regions. This kind of reduces collision hazards evenly along the orbit [67,68]. orbit and its building procedure have been proposed for consistent separation distance, which in turn reduces collision hazards evenly along the orbit [67,68].

Figure 11.11. IllustrationIllustration ofof TDX-TSXTDX-TSX flightflight formation:formation: (left) Formation-buildingFormation-building procedures (from leftleft toFigure right):right): 11. identical Illustration orbits, of TDX-TSX horizontalhorizontal flight plane formation: rotation, ( left eccentricity) Formation-building offset, offset, and procedures perigeeperigee rotation.rotation. (from left( right ) Helixto right): trajectorytrajectory identical inin the theorbits, relative relative horizo coordinates coordinatesntal plane (numbered rotation, (numbe eccentricityred axis: axis: angular angular offset, position andposition perigee in orbit, in orbit,rotation. unnumbered unnumbered (right axes:) along-trackaxes:Helix along-track trajectory and cross-track inand the cross-track relative position). coordinates position). Source: (numbeSource: DLR.red DLR. axis: angular position in orbit, unnumbered axes: along-track and cross-track position). Source: DLR. The remote sensing data obtained from TSX/TDX missions have been widely shared with and The remote sensing data obtained from TSX/TDX missions have been widely shared with and studiedThe by remote the scientific sensing community data obtained including from TSX/TDX the TanDEM-X missions Forest have/Non-Forest been widely Map shared available with and free of studied by the scientific community including the TanDEM-X Forest/Non-Forest Map available free chargestudied online by the [25 scientific,69]. Di ffcommunityerencing digital including elevation the TanDEM-X models taken Forest/Non-Forest at different moments Map available in time free can be of charge online [25,69]. Differencing digital elevation models taken at different moments in time can appliedof charge to monitoronline [25,69]. climate Differencing change, for digital example, elevat inion polar models regions. taken For at different the first moments time, pan-Arctic in time can InSAR be applied to monitor climate change, for example, in polar regions. For the first time, pan-Arctic isbe made applied possible to monitor with TDX climate and change, was applied for example, to observations in polar regions. of a thaw For slump the first in the time, Mackenzie pan-Arctic River InSAR is made possible with TDX and was applied to observations of a thaw slump in the Mackenzie Delta,InSAR Canada is made whose possible aerial with photo TDXis and provided was applied in Figure to observations 12A[70,71]. of The a thaw swamp slump whose in the DEM Mackenzie was taken River Delta, Canada whose aerial photo is provided in Figure 12A [70,71]. The swamp whose DEM inRiver 2015, Delta, shown Canada in Figure whose 12B, aerial has grownphoto is in provided size compared in Figure to 12A 2011, [70,71]. which The is represented swamp whose by negativeDEM was taken in 2015, shown in Figure 12B, has grown in size compared to 2011, which is represented heightwas taken changes in 2015, (depression) shown in in Figure Figure 12B, 12C. has In additiongrown in to size this compared differential to InSAR2011, which (DInSAR), is represented polarimetric by negative height changes (depression) in Figure 12C. In addition to this differential InSAR InSARby negative (Pol-InSAR) height by changes TSX/TDX (depression) enables multi-temporal, in Figure 12C. detailed In addition vertical to mappingthis differential of croplands InSAR and (DInSAR),(DInSAR), polarimetricpolarimetric InSAR (Pol-InSAR)(Pol-InSAR) by by TSX/TDX TSX/TDX enables enables multi-temporal, multi-temporal, detailed detailed vertical vertical wetlands, which is further discussed in Section4[ 72–74]. Lastly, 3D SAR images can be constructed mappingmapping of of croplands croplands and wetlands, whichwhich is is further further discussed discussed in inSection Section 4 [72–74]. 4 [72–74]. Lastly, Lastly, 3D 3DSAR SAR from multitudes of 2D SAR images taken at slightly different angles, which reduces ambiguity in imagesimages can can be be constructed constructed from multitudesmultitudes of of 2D 2D SA SARR images images taken taken at atslightly slightly different different angles, angles, which which pixels with the identical range from satellite but different terrain elevations. This technique of SAR reducesreduces ambiguity ambiguity inin pixelspixels with thethe identicalidentical range range from from satellite satellite but but different different terrain terrain elevations. elevations. tomography is being applied to deformation analysis of rigid bodies including glaciers and urban ThisThis technique technique of of SAR SAR tomography being being applied applied to to deformation deformation analysis analysis of rigidof rigid bodies bodies including including infrastructure, as shown in Figure 13[70,75]. glaciersglaciers and and urban urban infrastructure,infrastructure, asas shownshown in in Figure Figure 13 13 [70,75]. [70,75].

FigureFigure 12. 12.Mackenzie Mackenzie River Delta, Canada: Canada: (A (A) )Aerial Aerial snapshot snapshot of ofa thaw a thaw slump. slump. (B) (Sentinel-2B) Sentinel-2 L1C. L1C. Figure 12. Mackenzie River Delta, Canada: (A) Aerial snapshot of a thaw slump. (B) Sentinel-2 L1C. ImageImage containing containing the the slump slump in in August August 2017. 2017. ( C(C) Digital) Digital elevation elevation model model (DEM) (DEM) processing processing results results after single-passImageafter single-pass containing TanDEM-X TanDEM-X the sl observationump observation in August in June in2017. June 2015. ( C2015.) Source: Digital Source: ETHelevation ETH Zurich. Zurich. model (DEM) processing results after single-pass TanDEM-X observation in June 2015. Source: ETH Zurich.

Remote Sens. 2020, 12, 2546 12 of 31 Remote Sens. 2020, 12, x FOR PEER REVIEW 12 of 31

FigureFigure 13. 13.3D 3D point point cloudcloud representingrepresenting parameters esti estimatedmated from from SAR SAR tomographic tomographic inversion inversion on on a. a. StackStack of of 50 TerraSAR-X50 TerraSAR-X images images over Barcelona,over Barcelona, Spain: (Spain:left) Ground (left) height.Ground (right height.) Average (right deformation) Average rate.deformation Source: ETH rate. Zurich.Source: ETH Zurich.

TheThe nominal nominal design design life life ofof TSXTSX andand TDXTDX spacecraftspacecraft has ended ended in in 2012 2012 and and 2015, 2015, but but as as of of March March 2016,2016, the the two two spacecraft spacecraft werewere stillstill operationaloperational with similar similar amounts amounts of of residual residual propellant propellant (TSX: (TSX: 55%, 55%, TDX:TDX: 56%) 56%) [ 76[76].]. The The fact fact thatthat calibrationcalibration of radar instruments did did not not show show any any signs signs of of degradation degradation impliesimplies the the future future possibility possibility ofof extendingextending the lifetimelifetime of of a a medium-sized medium-sized SAR SAR spacecraft spacecraft if ifdesired; desired; on-orbiton-orbit servicing servicing was was first first demonstrated demonstrated to refuel to refuel a communications a satellite in 2020 in [ 772020]. The [77]. residual The capacityresidual of capacity onboard of lithium-iononboard lithi batteriesum-ion batteries is a function is a function of time, of gauging time, gauging 74% and 74% 82% and of82% the of initial the 108initial Ah for108 TSXAh for and TSX TDX, and respectively. TDX, respectively. The available The available spacecraft spacecraft power power has decreased has decreased from from the peakthe powerpeak power of 1.8 kWof 1.8 at kW the at beginning the beginning of life of (BOL) life (BOL) to the to orbitalthe orbital average average of 800 of 800 watts watts at theat the end end of of life (EOL),life (EOL), which which could could affect affect the capability the capability of radar of radar radiation radiation and and data data communications. communications. The The design design life oflife smaller of smaller SAR satellites SAR satellites is significantly is significantly shorter sh (

3.1.4.3.1.4. HJ-1C HJ-1C BeingBeing China’s China’s first first civilian civilian radarradar satellite,satellite, HJ-1C is part part of of the the HJ-1 HJ-1 (Environment-1) (Environment-1) constellation constellation implementedimplemented by by the the National National CommitteeCommittee forfor Disaster Reduction Reduction and and State State Environmental Environmental Protection Protection AdministrationAdministration (NDRCC (NDRCC/SEPA)/SEPA) [79 [79].]. HJ-1A HJ-1A and and HJ-1B HJ-1B are opticalare optical satellites satellites with awith hyperspectral a hyperspectral camera andcamera an infrared and an camera,infrared respectively;camera, respectively; they were they launched were launched together together in 2018 in and 2018 placed and placed into a circularinto a Sun-synchronouscircular Sun-synchronous orbit with orbit a 650 with km a altitude,650 km altitude, 4-day repeating 4-day repeating (recursive) (recursive) ground ground tracks, tracks, and an and an angular position difference of 180°. On the other hand, HJ-1C has a launch mass of 890 kg, angular position difference of 180◦. On the other hand, HJ-1C has a launch mass of 890 kg, nearly twice asnearly heavy twice as the as other heavy optical as the satellitesother optical (470 satellites kg), and (470 was kg), launched and was into launched a different into Sun-synchronous a different Sun- circularsynchronous orbit with circular a 500 orbit km altitude with a and500 31-daykm altitude repeating and cycles.31-day HJ-1Crepeating has acycles. dawn-dusk HJ-1C orbit,has a meaningdawn- thatdusk its orbit, LTDN meaning (Local Timethat its on LTDN Descending (Local Time Node) on is Descending 06:00 h, which Node) is alsois 06:00 diff h,erent which from is also 10:45 different h of the from 10:45 h of the other satellite. The three satellites are heterogeneous, as the “2 + 1 constellation” other satellite. The three satellites are heterogeneous, as the “2 + 1 constellation” notation suggests, notation suggests, but share common mission goals of environmental protection and disaster but share common mission goals of environmental protection and disaster monitoring. Examples of monitoring. Examples of disaster monitoring include flood, drought, typhoons, earthquakes, disaster monitoring include flood, drought, typhoons, earthquakes, grassland or forest fires, and oil grassland or forest fires, and oil spills [80]. The flexibility of HJ-1A to vary its orbit-repeating period spills [80]. The flexibility of HJ-1A to vary its orbit-repeating period between 4 and 31 days suggests between 4 and 31 days suggests synchronized interoperability with HJ-1C, which has a 31-day repeat synchronized interoperability with HJ-1C, which has a 31-day repeat cycle. The S-band SAR was cycle. The S-band SAR was developed with the assistance of , jointly from NPO developed with the assistance of Russia, jointly from NPO Mashinostroyenia (rocket design bureau) Mashinostroyenia (rocket design bureau) and Engineering Corporation. The radar and Vega Radio Engineering Corporation. The radar powered by two 40 Ah batteries experienced powered by two 40 Ah batteries experienced limited functionality due to antenna damage prior to limiteddecommissioning functionality [81]. due The to antenna impacts damage of such prior unit to malfunctions decommissioning would [81 be]. Theconfined impacts in ofa suchmission unit malfunctionsutilizing swarms would of besmall confined SAR satellites in a mission where utilizing a unit swarmsmay be ofcommissioned small SAR satellites or decommissioned where a unit mayflexibly. be commissioned or decommissioned flexibly.

Remote Sens. 2020, 12, 2546 13 of 31

3.2. Minisatellites Alike medium/large satellites, existing SAR minisatellites have been launched one-at-a-time despite their volume and mass footprints reduced from medium/large satellites. Actually, minisatellites were just at the verge of enabling a multiple satellite launch onboard a single launch vehicle, which was realized in smaller SAR satellites later.

3.2.1. NovaSAR-1 (400 kg) Developed by Surrey Satellite Technology Ltd. (SSTL) and Astrium UK, NovaSAR-1 is one of the first low-cost SAR satellites that are both small and commercial [82]. Potential use cases of NovaSAR-1 imagery include tropical forest protection, disaster monitoring, and maritime services to detect ships, icebergs, and oil spills [83,84]. The observation modes of NovaSAR-1 and their characteristics are summarized in Table5[ 85]. The originally envisioned constellation had three “NovaSAR-S” satellites operating in the S band. Only one satellite, named NovaSAR-S 1 or NovaSAR-1, has been in orbit since 2018. The operational parameters and the revisit performance for each observation mode are provided in Table5. The expected constellation performance shows that the e ffect of decreasing average revisit time is around a factor of 3; the effect of decreasing maximum revisit time is larger, meaning that week-long revisits are prevented and global monitoring becomes more continuous. The baseline modes in Table5 use HH or VV polarization, but the payload of NovaSAR can be configured to operate with dual polarization (any 2 from HH, VV, HV, or VH), tri-polarization (any 3 from HH, VV, HV, or VH), or fully-quad polarization (HH, VV, HV, and VH) as well.

Table 5. NovaSAR observation modes and 1-satellite/3-satellite revisit performance.

Av. Revisit Max. Revisit Observation Mode Resolution (m) Swath (km) Look Angle ( ) ◦ Time (Day) Time (Day) 1. ScanSAR 20 m 50–100 16–30 3.7 (1.5), 2.5 14 (3.5), 4 × × 2. Maritime surveillance 30 m 750 48–73 0.9 (0.3), 3.0 8 (0.5), 16 × × 3. Stripmap 6 m 13–20 16–31 3.2 (1.1), 2.9 12.5 (3.5), 3.4 × × 4. ScanSAR wide 30 m 55–140 15–32 3.7 (1.2), 3.1 13 (3.5), 3.7 × ×

As shown in Figure 12A, NovaSAR-1 has a 3 m 1 m microstrip patch array antenna with × 18 elements operating at 3.1–3.3 GHz in center frequency. This S band is located between the L band and the C band but has been seldom utilized since USSR’s Almaz-1 program whose operations terminated in 1992 [9]. An S-band system has operating wavelengths closest to existing C-band systems in particular, suggesting similarly diverse applications already served by C-band systems. While HJ-1C is another example of exploiting S-band frequencies, NovaSAR-1 concentrated on reducing the satellite mass by employing COTS hardware. In lieu of traveling-wave tube amplifiers that are both bulky and high-voltage, NovaSAR-1 used allium nitride (GaN) solid-state power amplifiers. The radio frequency peak power of NovaSAR-1 is a 1.8 kW, 10% to 15% of a Cosmo-SkyMed satellite, where the power subsystem mass was reduced by limiting the duration of each SAR operation to 2 min per orbit. Although much shorter than the 10-min continuous operation of a COSMO satellite, the duration is still sufficient to cover a nation-state in most cases. Through these miniaturization measures, the interior of NovaSAR-1 still has unoccupied space, as shown in the middle of Figure 14 (left), with further miniaturizablity for an active beam-steering SAR satellite. Figure 14 (right) shows a SAR image capturing the vicinity of the Suez Canal at 30 m resolution. The Commonwealth Scientific and Industrial Research Organisation (CSIRO) of Australia has purchased 10% share of NovaSAR’s acquisition time to improve flood forecasting systems [86]. Similar to larger SAR missions such as COSMO-SkyMed and TSX/TDX, NovaSAR adopted Sun-synchronous orbits with LTAN at 10:30 am. This Sun synchronism is a common practice in designing Earth-observing optical satellites because of advantages in power generation and thermal controls, which is the same for SAR satellites. From a Remote Sens. 2020, 12, 2546 14 of 31

Remote Sens. 2020, 12, x FOR PEER REVIEW 14 of 31 remote sensing perspective, temperature or moisture conditions, as well as solar illumination, tend to for SAR satellites. From a remote sensing perspective, temperature or moisture conditions, as well as be consistent in ground targets if observed at the same time of the day. solar illumination, tend to be consistent in ground targets if observed at the same time of the day.

FigureFigure 14. 14.Rendition Rendition ofof NovaSAR-1NovaSAR-1 and its SAR imagery: ( (leftleft)) Antenna Antenna array, array, internal internal components, components, solarsolar panels. panels. ( right(right)) Scene Scene of of Suez Suez Canal Canal and and the the Red Red Sea Sea obtained obtained in the in ScanSARthe ScanSAR mode. mode. Source: Source: SSTL, AirbusSSTL, Airbus DS. DS.

AlthoughAlthough aa DneprDnepr rocketrocket maymay launchlaunch up to 3 NovaSAR at once theoretically, theoretically, multi-satellite multi-satellite launcheslaunches have have notnot beenbeen realizedrealized forfor NovaSARNovaSAR andand other minisatellites; furt furtherher miniaturization miniaturization was was necessary,necessary, which which was was achieved achieved by microsatellitesby microsatellites introduced introduced in the in next the section. next section. The notable The milestonenotable ofmilestone NovaSAR, of however,NovaSAR, is thathowever, SSTL becameis that theSSTL first became satellite the manufacturer first satellite with manufacturer a full Earth-observation with a full line-upEarth-observation covering radar line-up instruments covering as radar well asinstruments infrared and as visible-wavelengthwell as infrared and payloads visible-wavelength (e.g., Disaster Monitoringpayloads (e.g., Constellation Disaster Monitoring in 2002). Continuing Constellation its successful in 2002). contracts Continui ofng optical its successful satellites contracts with several of nationaloptical satellites governments, with several SSTL was national able to govern commercializements, SSTL NovaSAR’s was able product to commercialize with Australia NovaSAR’s and the Philippines,product with heralding Australia the and advent the Philippines, of a global heraldin SAR datag the market advent [87 of]. a global SAR data market [87].

3.2.2.3.2.2. TECSARTECSAR (260(260 kg)kg) TECSAR,TECSAR, also also transcribed transcribed as as TechSAR, TechSAR, is is the the first first Israeli Israeli SAR SAR satellite satellite designed designed and and developed developed by Israelby Israel Aerospace Aerospace Industries Industries Ltd. Ltd. (IAI) (IAI) for for technology technology demonstration demonstration ofof Isra Israelieli Ministry Ministry of of Defense. Defense. TECSAR-1, also called -8, was launched in 2008 onto a 403 km 581 km orbit with 41 inclination TECSAR-1, also called Ofeq-8, was launched in 2008 onto a 403 km × 581 km orbit with 41°◦ inclination whereas TECSAR-2, or Ofeq-10, was launched in 2014 onto a 384 km 609 km orbit with 140.95 whereas TECSAR-2, or Ofeq-10, was launched in 2014 onto a 384 km × 609 km orbit with 140.95° ◦ inclinationinclination [[88].88]. Out Out of of the the satellite satellite mass mass of 260 of 260kg, the kg, SAR the payload SAR payload accounts accounts for 100 forkg with 100 kg1.6 withkW 1.6peak kW power, peak which power, is whichpowered is poweredby a 45 Ah by lithium-ion a 45 Ah lithium-ionbattery with batterysolar panels with capable solar panels of generating capable of850 generating W of power 850 W[89]. of This power level [89 of]. Thisminiaturization level of miniaturization has been realized has beenby adopting realized a by deployable, adopting a deployable,umbrella-shaped umbrella-shaped parabolic antenna. parabolic The antenna. reflector-based The reflector-based parabolic antenna parabolic of TECSAR antenna distinguishes of TECSAR distinguishesitself from active itself frompatch active arrays patch of arraysTerraSAR-X of TerraSAR-X and Cosmo-SkyMed and Cosmo-SkyMed constellations constellations [90–92]. [90 The–92 ]. Theparaboloid paraboloid reflector reflector consists consists of skeleton of skeleton ribs and ribs knitted and knitted mesh, mesh, the latter the latterof which of which weighs weighs less than less than0.5 kg 0.5 in kg mass. in mass. At the At center the center of the ofparaboloid the paraboloid is a rigid is adish rigid made dish of made carbon of carbonfiber reinforced fiber reinforced plastic plastic(CFRP) (CFRP) to combine to combine its advantage its advantage in surface in surface homogeneity homogeneity with withthe lightweight the lightweight of knitted of knitted mesh mesh in inFigure Figure 15 15 (left) (left) [93]. [93]. Among Among the the observation observation mo modesdes of of TECSAR, TECSAR, the the wide-coverage wide-coverage ScanSAR ScanSAR mode mode achievesachieves the the largest largest swath swath upup toto 100100 kmkm with a resolution between 8 8 m m and and 20 20 m. m. The The stripmap stripmap mode, mode, mosaicmosaic mode, mode, and and spotlight spotlight mode mode allocate allocate observation observation time time to ato band a band area, area, several several points, points, and aand single a ,single respectively. spot, respectively. The resulting The resulting resolution resolu decreasestion decreases from 3 from m to 3 1.8 m mto and1.8 m 1 m.and 1 m.

Remote Sens. 2020, 12, 2546 15 of 31 Remote Sens. 2020, 12, x FOR PEER REVIEW 15 of 31 Remote Sens. 2020, 12, x FOR PEER REVIEW 15 of 31

Figure 15. TECSAR and its observation modes: (left) Assembly. (right) Wide-coverage mode, strip FigureFigure 15. 15. TECSARTECSAR and and its its observation observation modes: ((leftleft)) Assembly.Assembly. ( right(right) Wide-coverage) Wide-coverage mode, mode, strip strip mode, mode, mosaic mode, and spotlight mode. Source: IAI, Ltd. mode,mosaic mosaic mode, mode, and and spotlight spotlight mode. mode. Source: Source: IAI, IAI, ELTA ELTA Systems Systems Ltd. Ltd. 3.2.3. SmallSat InSAR (180 kg) 3.2.3. SmallSat InSAR (180 kg) SmallSat InSARInSAR is is a designa design concept concept by Jetby Propulsion Jet Propulsion Laboratory Laboratory (JPL) to (JPL) demonstrate to demonstrate the technical the SmallSat InSAR is a design concept by Jet Propulsion Laboratory (JPL) to demonstrate the feasibilitytechnical feasibility and economic and viabilityeconomic of aviability small-satellite of a small-satellite SAR constellation SAR [ 46constellation]. Its design [46]. principles Its design were technical feasibility and economic viability of a small-satellite SAR constellation [46]. Its design alreadyprinciples explained were already in Section explained2, whose in Section volume 2, and whose mass volume constraints and mass are derived constraints from are the derived standards from of principles were already explained in Section 2, whose volume and mass constraints are derived from anthe EELVstandards Secondary of an EELV Payload Secondary Adapter Payload (“ESPA” Adapter or “ESPA (“ESPA” ring”), or which “ESPA utilizes ring”), the which unused utilizes payload the the standards of an EELV Adapter (“ESPA” or “ESPA ring”), which utilizes the marginsunused payload of Evolved margins Expendable of Evolved Launch Expendable Vehicles Laun (EELVs)ch Vehicles of the (EELVs) US Department of the US of Department Defense [94 of]. unused payload margins of Evolved Expendable Launch Vehicles (EELVs) of the US Department of MultipleDefense [94]. types Multiple of ESPA types rings of andESPA their rings combinations and their combinations will provide will small provide satellites small with satellites affordable with Defense [94]. Multiple types of ESPA rings and their combinations will provide small satellites with rideshareaffordable (orrideshare piggy-back) (or piggy-back) launch opportunities launch opport depictedunities in depicted Figure 16 in[ 95Figure]. Although 16 [95]. anAlthough ESPA and an affordable rideshare (or piggy-back) launch opportunities depicted in Figure 16 [95]. Although an anESPA ESPA and “grande” an ESPA “grande” may allow may the allow maximum the maximum spacecraft spacecraft mass of mass 320 kgof 320 and kg 450 and kg 450 in kg 6-slot in 6-slot and ESPA and an ESPA “grande” may allow the maximum spacecraft mass of 320 kg and 450 kg in 6-slot 4-slotand 4-slot configurations, configurations, respectively, respectively, SmallSat SmallSat InSAR InSAR aimed aimed to drive to drive the the spacecraft spacecraft mass mass below below 200 200 kg and 4-slot configurations, respectively, SmallSat InSAR aimed to drive the spacecraft mass below 200 accommodatablekg accommodatable by by all all six six slots slots of of an an ESPA ESPA ring ring at at the the same same time. time. By By limitinglimiting thethe spacecraftspacecraft mass kg accommodatable by all six slots of an ESPA ring at the same time. By limiting the spacecraft mass and size (1.0 m × 0.7 m × 0.60.6 m), m), shown shown in Figure 16 (right), multiple SAR satellites can be launched and size (1.0 m × 0.7× m × 0.6× m), shown in Figure 16 (right), multiple SAR satellites can be launched simultaneously for for rapid rapid constellation constellation deployment. deployment. SmallSat SmallSat InSAR InSAR considered considered deploying deploying a total a total of simultaneously for rapid constellation deployment. SmallSat InSAR considered deploying a total of of12 12small small SAR SAR satellites satellites with with two two ESPA ESPA launches, launches, but but its its launch launch schedule schedule is unknown. The peak 12 small SAR satellites with two ESPA launches, but its launch schedule is unknown. The peak transmit power of the satellite isis designeddesigned toto bebe 11 kW.kW. transmit power of the satellite is designed to be 1 kW.

Figure 16. Accommodation of secondary payloads in Evolved Expendable Launch Vehicle Secondary Figure 16. Accommodation of secondary payloads in Evolved Expendable Launch Vehicle Secondary FigurePayload 16. Accommodation Adapter (ESPA) of rings: secondary (left) Stowage payloads examples in Evolved for Expendable different launch Launch vehicles. Vehicle (right Secondary) Volume Payload Adapter (ESPA) rings: (left) Stowage examples for different launch vehicles. (right) Volume Payloadconstraints Adapter for (ESPA) similar-sized rings: payloads.(left) Stowage Source: examples NASA /forJPL. different launch vehicles. (right) Volume constraints for similar-sized payloads. Source: NASA/JPL. constraints for similar-sized payloads. Source: NASA/JPL. SmallSat InSAR is often compared with the NASA-ISRO Synthetic Aperture Radar (NISAR) SmallSat InSAR is often compared with the NASA-ISRO Synthetic Aperture Radar (NISAR) Mission in terms of scientific scopes, mass, and cost. The NISAR mission scheduled for launch in 2021 Mission in terms of scientific scopes, mass, and cost. The NISAR mission scheduled for launch in 2021

Remote Sens. 2020, 12, 2546 16 of 31

RemoteSmallSat Sens. 2020, 12 InSAR, x FORis PEER often REVIEW compared with the NASA-ISRO Synthetic Aperture Radar (NISAR)16 of 31 Mission in terms of scientific scopes, mass, and cost. The NISAR mission scheduled for launch in 2021 hashas multiplemultiple purposespurposes of of measuring measuring land land surface surf motionsace motions and ecosystem and ecosystem disturbances. disturbances. These objectives These objectivescan be translated can be into translated use scenarios into specificuse scenarios to India sp suchecific as monitoringto India such agricultural as monitoring biomass, agricultural Himalayan biomass,glaciers, andHimalayan coastal environmentsglaciers, and [coastal96]. The environments main objective [96]. of SmallSat The main InSAR objective is to mapof SmallSat Earth’s surfaceInSAR isdeformation to map Earth’s with sub-millimeter-per-yearsurface deformation with precision sub-millimeter-per-year via daily visits supported precision by avia twelve-satellite daily visits supportedconstellation. by a A twelve-satellite rough estimate conste of thellation. total system A rough cost estimate is 1 to 1.5of the times total the system cost of cost a single-spacecraft is 1 to 1.5 times theNISAR cost mission.of a single-spacecraft The JPL team’s NISAR work datingmission. back The to JP 1999L team’s is based work on adating systems-engineering back to 1999 is based philosophy on a systems-engineeringbriefly described in Sectionphilosophy2[ 45 ].briefly The idea described of systemizing in Section the 2 design [45]. The process idea of of SAR systemizing satellites andthe design process of SAR satellites and relaxing their design goal for miniaturization was referred to by relaxing their design goal for miniaturization was referred to by designers of RADARSAT, TSX/TDX, designers of RADARSAT, TSX/TDX, and Micro XSAR to name a few [97–100]. and Micro XSAR to name a few [97–100].

3.2.4.3.2.4. Micro Micro XSAR XSAR (135 (135 kg) kg) JAXA/ISAS,JAXA/ISAS, University University of of Tokyo, Tokyo, and and Keio Keio Univ Universityersity are are working working on on the the 100 100 kg kg class class X-band X-band SARSAR project project whose whose proto-flight proto-flight model model (PFM) (PFM) was was completed completed in 2019 in and 2019 is andcurrently is currently ready for ready launch for [101].launch A [ 101novel]. A signal novel signalprocessing processing scheme scheme as well as wellas an as efficient an efficient waveguide waveguide feeder feeder design, design, with with an an increasedincreased chirp chirp bandwidth ofof 300300 MHz,MHz, isis capablecapable ofof providingproviding 1-m 1-m resolution resolution at at nadir nadir o ffoff-set-set angle angle of of 30° [102–104]. Figure 17 (left) illustrates the concept of operations where active or wide-area 30◦ [102–104]. Figure 17 (left) illustrates the concept of operations where active or wide-area sensing is sensingmade during is made the during day and the passiveday and Earth-orientedpassive Earth-orie sensingnted sensing is made is at made night. at Figurenight. Figure17 (right) 17 (right) shows showspossible possible daytime daytime observation observation modes, modes, which which include include underground underground mapping. mapping.

FigureFigure 17. 17. MissionMission concept concept of of Micro-XSAR: Micro-XSAR: (left (left) )Attitude Attitude control control in in orbit. orbit. (right (right) )Observation Observation modes. modes. Source:Source: JAXA. JAXA. To supply SAR power more than 1.3 kW for several minutes, during the daytime, the solar cells To supply SAR power more than 1.3 kW for several minutes, during the daytime, the solar cells of Micro XSAR charge their lithium-ion battery whose discharge specification is rated at 3 C or the of Micro XSAR charge their lithium-ion battery whose discharge specification is rated at 3 C or the speed of depleting the whole battery in 1/3 h [105]. The estimated battery energy is 400 Wh and the speed of depleting the whole battery in 1/3 h [105]. The estimated battery energy is 400 Wh and the ampere-hour capacity is expected to be similar to or less than TECSAR whose design specifications ampere-hour capacity is expected to be similar to or less than TECSAR whose design specifications are summarized in Table6. Amongst the other satellites in Table6, Radar In a CubeSat (RaInCube) are summarized in Table 6. Amongst the other satellites in Table 6, Radar In a CubeSat (RaInCube) provides the lower capacity bound of about 10 Ah (similar to an electric scooter) for smaller SAR provides the lower capacity bound of about 10 Ah (similar to an electric scooter) for smaller SAR satellites discussed in the next subsection [106–108]. Further advances in power source densities could satellites discussed in the next subsection [106–108]. Further advances in power source densities bring both the cost and footprints down to intensify the advantages of small SAR satellite systems. could bring both the cost and footprints down to intensify the advantages of small SAR satellite systems. Table 6. Power and mass of different SAR missions from nanosatellites to medium satellites.

Table 6. Power andBattery mass of differentSolar Array SAR missionsPayload from Peak nanosatellites to mediumTotal satellites. Launch Mission Payload Mass Capacity Power Power Mass Battery Solar Array Payload Peak Payload Total Launch MissionRaInCube ~10 Ah 45 W 22 W 5.5 kg 12 kg Capacity Power Power Mass Mass TECSAR 45 Ah 1600 W 850 W 100 kg 260 kg RaInCube ~10 Ah 45 W 22 W 5.5 kg 12 kg HJ-1C 80 Ah 1100 W - 200 kg 890 kg TECSARSAR-Lupe 45 108Ah Ah 1600 - W 1800 850 W W 394 100 kg kg 1230 260 kgkg HJ-1CTSX 80 132Ah Ah 1100 - W - - 200 - kg 770 890 kg kg SAR-LupeCosmo-SkyMed 108336 Ah Ah 40,000 - W 7000 1800 W W 394 - kg 1700 1230 kg kg TSX 132 Ah - - - 770 kg Cosmo- 336 Ah 40,000 W 7000 W - 1700 kg SkyMed

Remote Sens. 2020,, 12,, 2546x FOR PEER REVIEW 17 of 31

3.3. Microsatellites 3.3. Microsatellites Sub-100 kg microsatellites are currently the lightest small-satellite class in which SAR has been Sub-100 kg microsatellites are currently the lightest small-satellite class in which SAR has been implemented. Many of these SAR satellites are being developed by start-up companies for implemented. Many of these SAR satellites are being developed by start-up companies for commercial commercial purposes and feature rapid design iterations between generations. purposes and feature rapid design iterations between generations.

3.3.1. -X1/X2 ICEYE-X1/X2 (85 kg) Developed by ICEYE in and launched in 2018, ICEYE-X1 is known as the firstfirst SAR in microsatellite class with a design mass of 70 kg as as we wellll as as the the country’s country’s first first commercial commercial satellite satellite [109]. [109]. In its launchlaunch configuration,configuration, ICEYE-X1 has a size of 0.7 mm (H)(H) × 0.6 m (W) × 0.4 m (D); its X-band × × antenna hashas aa lengthlength ofof 3.253.25 mm when when deployed deployed [ 110[110,111].,111]. With With 2 2 to to 3 years3 years of of designed designed life, life, ICEYE-X1 ICEYE- hasX1 has a similar a similar shape shape as the as Micro the XSARMicro proto-flightXSAR proto-flight model or model the SmallSat or the InSARSmallSat concept. InSAR Compared concept. toCompared this proof-of-concept to this proof-of-concept version, ICEYE-X2 version, ICEYE-X2 features increased features increased form factors form (0.8 factors m 0.8(0.8m m × 0.60.8 m × × before× 0.6 m deployment, before deployment, 85 kg) to85 improvekg) to improve the SAR the performance, SAR performance, as shown as shown in Figure in Figure 18. The 18. RF The peak RF powerpeak power of ICEYE-X2 of ICEYE-X2 is 4 kW, is more4 kW, than more twice than the tw ICEYE-X1ice the ICEYE-X1 capacity, andcapacity, its SAR and imagery its SAR resolution imagery alsoresolution improved also fromimproved 10 m from to a sub-meter10 m to a sub-meter level [112]. level The [112]. fast design The fast iteration design caniteration be seen can from be seen the launchfrom the dates launch of thedates two of satellites,the two satellites, January Januar 2018 andy 2018 December and December 2018, separated 2018, separated by less by than less a than year. Thea year. follow-on The follow-on satellites, satellites, ICEYE-X4 ICEYE-X4 and ICEYE-X5, and ICEY haveE-X5, identical have designidentical specifications design specifications as ICEYE-X2 as andICEYE-X2 have been and have launched been togetherlaunched in together July 2019, in July which 2019, is probably which is theprobably first case the offirst launching case of launching multiple SARmultiple satellites SAR satellites simultaneously. simultaneously. The ICEYE-X3, The ICEYE- alsoX3, called also Harbinger, called Harbinger, is a military-purpose is a military-purpose variant featuringvariant featuring field-effect field-effect electric propulsion electric propulsion and high-rate and laser high-rate communications laser communications capabilities whose capabilities payload operationswhose payload demand operations 3 kW peak demand power. 3 HarbingerkW peak ispowe no longerr. Harbinger classified is asno a longer microsatellite classified because as a itsmicrosatellite launch mass because is 150 kgits fallinglaunch intomass the is minisatellite150 kg falling class. into All the ICEYE minisatellite spacecraft class. except All X3ICEYE use spacecraft except X3 use Sun-synchronous orbits with inclination values of 97.56° or 97.77°; ICEYE- Sun-synchronous orbits with inclination values of 97.56◦ or 97.77◦; ICEYE-X3 instead uses an inclined X3 instead uses an inclined orbit with 40.0° for increased visit frequencies in mid- to low-latitude orbit with 40.0◦ for increased visit frequencies in mid- to low-latitude regions [113]. The fully-blown constellation,regions [113]. The with fully-blown a total of 18 constellation, ICEYE satellites with a launched total of 18 by ICEYE 2021, satellit will providees launched an average by 2021, of will 3-h revisitprovide interval an average around of 3-h the revisit globe interval to observe around sea ice the movements, globe to observe marine sea oil ice spills, movements, and illegal marine fishing oil vessels.spills, and In illegal addition fishing to its vessels. fast design In addition iteration, to its the fast fact design that iteration, ICEYE is the the fact first that Finnish ICEYE commercial is the first satelliteFinnish exemplifiescommercial a satellite strategy exemplifies of jumpstarting a strategy the SAR of satellite jumpstarting development, the SAR instead satellite of optical development,/infrared observationinstead of satellites,optical/infrared for Earth observation remote sensing satellites, and its datafor commercialization.Earth remote sensing and its data commercialization.

Figure 18. ICEYE series: (left) ICEYE-X1. (middle) ICEYE-X2, X4, X5. (right) ICEYE-X3 (Harbinger). Figure 18. ICEYE series: (left) ICEYE-X1. (middle) ICEYE-X2, X4, X5. (right) ICEYE-X3 (Harbinger). Source: ICEYE, York Space Systems. Source: ICEYE, York Space Systems. 3.3.2. MicroSAR (65 kg) 3.3.2. MicroSAR (65 kg) The MicroSAR system is a proposal by Kongsberg Satellite Services and Space Norway, tailored for maritimeThe MicroSAR monitoring. system It is equipped is a proposal with by a C-band Kongsberg 800 W Satellite radar transmitter Services and and Space an onboard Norway, automatic tailored identificationfor maritime systemmonitoring. (AIS) forIt is vessel equipped tracking with [114 a ].C-band The launch 800 W mass radar of MicroSAR transmitter is 65and kg an including onboard a 3.8automatic m 1.8 identification deployable reflectorsystem (AIS) illustrated for vessel in Figure tracking 19 [114].(left). The Figure launch19 (right) mass of provides MicroSAR a pictorial is 65 kg × descriptionincluding a of3.8 expected m × 1.8 deployable revisit times reflector achieved illustrated by eightsatellites in Figure in 19 two (left). orbit Figure planes 19 in (right) the arctic provides region. a Low-latencypictorial description tasking andof expected data delivery revisit are times possible achieved via a by network eight satellites of twenty in ground two orbit stations planes adapted in the forarctic small region. satellites Low-latency across continents tasking and and data oceans deliver includingy are thepossible Arctic via Circle a network (Svalbard) of twenty and Antarctica ground (Trollstations Station). adapted Although for small any satellites MicroSAR across satellite continents has and not beenoceans launched including yet, the it Arctic represents Circle an (Svalbard) example ofand prioritizing Antarctica the (Troll ground Station). station Although infrastructures, any MicroSAR which have satellite been jointly has not utilized been bylaunched Cosmo-SkyMe yet, it represents an example of prioritizing the ground station infrastructures, which have been jointly utilized by Cosmo-SkyMe and NovaSAR. As the demand for SAR data increase and small satellites

Remote Sens. 2020, 12, 2546 18 of 31

Remote Sens. 2020, 12, x FOR PEER REVIEW 18 of 31 Remote Sens. 2020, 12, x FOR PEER REVIEW 18 of 31 and NovaSAR. As the demand for SAR data increase and small satellites play a bigger role therein, play a bigger role therein, its market will be segmented into launch services (e.g., Electron rocket), itsplay market a bigger will role be segmentedtherein, its intomarket launch will services be segm (e.g.,ented Electron into launch rocket), services ground (e.g., stations Electron (e.g., rocket), KSAT), ground stations (e.g., KSAT), data analytics (5. Discussion), and so forth dedicated to small satellites dataground analytics stations (5. (e.g., Discussion), KSAT), data and analytics so forth dedicated (5. Discussion), to small and satellites so forth and dedicated/or spaceborne to small SAR. satellites and/or spaceborne SAR.

Figure 19. MicroSAR: (left) Artist’s rendition. (right) Simulated revisit times in the Norwegian Sea Figure 19. MicroSAR: (leftleft)) Artist’sArtist’s rendition.rendition. ((rightright)) SimulatedSimulated revisitrevisit timestimes inin thethe NorwegianNorwegian SeaSea and the Greenland Sea. Source: Kongsberg Satellite Services. andand thethe GreenlandGreenland Sea.Sea. Source:Source: KongsbergKongsberg SatelliteSatellite Services.Services. 3.3.3. Capella X-SAR (48 kg) 3.3.3. Capella X-SAR (48 kg) This SARSAR constellation,constellation, developed by Capella Space, will have 36 satellites by 2023, 6 ofof whichwhich are alreadyThis SAR in orbitconstellation, [115]. The developed first satellite, by Capella Capella Space, 1 or Denali, will have has a36 launch satellites mass by of 2023, less 6 than of which 50 kg are already in orbit [115]. The first satellite, Capella 1 or Denali, has a launch mass of less than 50 kg withwith an origami-like antenna shown shown in in Figure Figure 2020 (left). (left). The The second second satellite, satellite, Capella Capella 2 or 2 orSequoia, Sequoia, is with an origami-like antenna shown in Figure 20 (left). The second satellite, Capella 2 or Sequoia, is2 is about twice as large as the predecessor, accommodates a 600 W transmitter and a mesh-based 8 m 2 about twice as large as the predecessor, accommodates a 600 W transmitter and a mesh-based 8m2 reflectorabout twice that as is large shown as inthe Figure predecessor, 20 (right) accommodates to achieve sub-meter a 600 W ground transmitter resolution and a [mesh-based116]. Following 8m reflectorreflector thatthat isis shownshown inin FigureFigure 2020 (right)(right) toto acachieve sub-meter ground resolutionlution [116].[116]. FollowingFollowing thethe launch of Capella Capella 1 1 in in December December 2018 2018 and and Capell Capellaa 2 2in in March March 2020, 2020, three three satellites satellites (Capella (Capella 3, 4, 3, 4,the 5) launch will be of launched Capella 1 with in December further design 2018 improvements,and Capella 2 in constituting March 2020, a three “Whitney satellites sub-constellation. (Capella 3, 4, 5) will be launched with further design improvements,ements, constitutingconstituting aa “Whitney“Whitney sub-constellation.sub-constellation. Another satellite called Capella X was launched into an inclined orbit with 45◦ inclination in May Another satellite called Capella X was launched into an inclined orbit with 45° inclination in May 2020. The Whitney sub-constellation and others will constitute the “Capella 36” constellation, and the coverage2020. The performanceWhitney sub-constellation of possible configurations and others will in betweenconstitute is the summarized “Capella 36” in Table constellation,7. Capella and Space the coveragecoverage performanceperformance ofof possiblepossible configurationsconfigurations inin between is summarized in Table 7. Capella Space isis usingusing thethe satellitesatellite groundground stationstation service provided by Amazon Web ServicesServices (AWS)(AWS) forfor thethe rapidrapid deliveryis using the ofsatellite satellite data ground to its station customers service [117 provided]. by Amazon Web Services (AWS) for the rapid delivery of satellite data to its customers [117].

Figure 20. Capella series: (left) Capella 1 (Denali). (right) Capella 2 (Sequoia). Source: Capella Space. Figure 20. Capella series: (leftleft)) CapellaCapella 11 (Denali).(Denali). ((rightright)) CapellaCapella 22 (Sequoia).(Sequoia). Source:Source: CapellaCapella Space.Space. Table 7. Capella X-SAR observation modes and 1-satellite/3-satellite revisit performance. Table 7. Capella X-SAR observation modes and 1-satellite/3-satellite revisit performance. Total # Satellites 6 12 24 36 Total # Satellites → 66 1212 2424 3636 # orbit# orbit planes planes 2 2 4 84 12 8 12 #Average orbit planes revisit (h) <4 2< 2 41 <1 8 12 Average revisit (h) <4 <2 1 <1 AverageMaximum revisit revisit (h) (h) 12 <4 6 <2 4 <2 1 <1 MaximumInSAR revisit revisit (h) 24 12 12 6 4 4 <2 InSARInSAR revisitrevisit (h)(h) 24 24 12 12 6 6 4 4

3.4. Nanosatellites Due to extreme sizing constraints, nanosatellitesllites useuse thethe Ku-bandKu-band oror higherhigher microwavemicrowave frequenciesfrequencies (~100(~100 GHz)GHz) thatthat areare increasinglyincreasingly sensitivesensitive toto precipitation.precipitation. TheThe sensitivitysensitivity ofof resonanceresonance

Remote Sens. 2020, 12, x FOR PEER REVIEW 19 of 31

bands (e.g., 60 GHz and 118 GHz for oxygen) to precipitation and altitude makes radar sounders that operate at these frequencies with short wavelengths more suitable for atmospheric sciences (e.g., tropical cyclones) than ground surface measurements [118]. Among those spectra, the Ka band is considered to achieve a good balance between high resolution and low attenuation and, therefore, Remotewas Sens. used2020 in, 12the, 2546 first radar CubeSat, Radar In a CubeSat (RaInCube). Its rain radar performance19 of 31of distinguishing isolated rain cells and strong rainstorms from ground echoes were in solid agreement with ground-based measurements [119]. The operation concept of the RainCube mission is 3.4. Nanosatellites summarized in Figure 21 (left). DueIn tothe extreme large-satellite sizingconstraints, class (>1 ton), nanosatellites the Surface use the Ku-bandand Ocean or higherTopography microwave (SWOT) frequencies satellite (~100(2022) GHz) will that use are the increasingly Ka band for sensitive SAR interferometry to precipitation. for The the sensitivity first time. of Short resonance wavelengths bands (e.g., at this 60 GHzhigh andfrequency 118 GHz enable for oxygen) precise to measurement precipitation andof wind-g altitudeenerated makes radarsurface sounders roughness, that as operate demonstrated at these frequenciespreviously with by airborne short wavelengths measurements more taken suitable by th fore National atmospheric Centre sciences for Space (e.g., Studies tropical (CNES) cyclones) in thanFrance ground and surface JPL [120]. measurements The mission [118 goal]. Amongis to provide those spectra,global measurements the Ka band is of considered continental to achievesurface a goodwater balancestorage betweenexceeding high 250 resolutionm2 in area and(lakes) low or attenuation 100 m in width and, therefore,(rivers) [121]. was Figure used in 21 the (right) first radarillustrates CubeSat, the Radar mission In concept a CubeSat of (RaInCube).the SWOT mission Its rain and radar the performance satellite whose of distinguishingantenna area isisolated smaller rainthan cells previous and strong SAR missions rainstorms due from to shorter ground waveleng echoesths. were Moreover, in solid agreementthe utilization with of ground-basedthe Ka band in measurementsvegetation canopy [119]. Themeasurement operation conceptwas demonstrated of the RainCube in ground mission tests is summarizedfor deciduous in and Figure coniferous 21 (left). trees [122].

FigureFigure 21. 21.Ka-band Ka-band SAR SAR in variousin various size size scales: scales: (left ()left RainCube) RainCube nanosatellite. nanosatellite. (right (right) Surface) Surface Water Water and Oceanand Ocean Topography Topography (SWOT) (SWOT) satellite. satellite. Source: Source: JPL/NASA, JPL/NASA, CNES. CNES.

InKu the and large-satellite Ka bands classhave (not>1 ton),been theexploited Surface in Water spaceborne and Ocean radar Topography as much as (SWOT)lower-frequency satellite (2022)spectra, will but use future the Ka nanosatellites band for SAR could interferometry make use of th forese thebands; first demonstration time. Short wavelengths of InSAR near at the this K highband frequency in the SWOT enable mission precise may measurement also be done of wind-generatedusing nanosatellites surface in proximity roughness, formation as demonstrated flight or previouslyconnected by with airborne a boom measurements [123]. taken by the National Centre for Space Studies (CNES) in and JPL [120]. The mission goal is to provide global measurements of continental surface water storage exceeding4. Applications 250 m2 ofin Small area (lakes)Satellite or SAR 100 mData in width (rivers) [121]. Figure 21 (right) illustrates the mission concept of the SWOT mission and the satellite whose antenna area is smaller than previous Biospheric monitoring has been considered as the primary scientific objective in large SAR SAR missions due to shorter wavelengths. Moreover, the utilization of the Ka band in vegetation missions such as NISAR, Biomass, and Tandem-L, which are planned for launch in the near future. canopy measurement was demonstrated in ground tests for deciduous and coniferous trees [122]. Small-satellite SAR has its own advantages of quick revisit time and near real-time coverage, which Ku and Ka bands have not been exploited in spaceborne radar as much as lower-frequency spectra, complement these planned missions and existing Earth-observation assets both in optical or but future nanosatellites could make use of these bands; demonstration of InSAR near the K band in microwave spectra. the SWOT mission may also be done using nanosatellites in proximity formation flight or connected with4.1. a Coverage boom [123 Enhancement]. with Small SAR Constellations

4. ApplicationsLarge SAR of spacecraft Small Satellite has more SAR functionalities Data than small satellites. For example, the NISAR mission, a NASA-ISRO joint Earth-observing initiative planned for launch in 2021, will for the first Biospheric monitoring has been considered as the primary scientific objective in large SAR missions time use dual radar frequencies (L-band and S-band) in a single spacecraft. Having rich flight heritage such as NISAR, Biomass, and Tandem-L, which are planned for launch in the near future. Small-satellite since the Seasat mission in 1978, NASA will provide the L-band (24 cm wavelength, 1.25 GHz) SAR SAR has its own advantages of quick revisit time and near real-time coverage, which complement these planned missions and existing Earth-observation assets both in optical or microwave spectra.

4.1. Coverage Enhancement with Small SAR Constellations Large SAR spacecraft has more functionalities than small satellites. For example, the NISAR mission, a NASA-ISRO joint Earth-observing initiative planned for launch in 2021, will for the first Remote Sens. 2020, 12, 2546 20 of 31 time use dual radar frequencies (L-band and S-band) in a single spacecraft. Having rich flight heritage Remote Sens. 2020, 12, x FOR PEER REVIEW 20 of 31 since the Seasat mission in 1978, NASA will provide the L-band (24 cm wavelength, 1.25 GHz) SAR while ISRO will provide the S-band (9.3 cm wavelength, 3.20 GHz) SAR, the satellite bus, and launch while ISRO will provide the S-band (9.3 cm wavelength, 3.20 GHz) SAR, the satellite bus, and launch services [124]. Figure 22 (left) illustrates the instruments of NISAR. The S-band SAR with a shorter services [124]. Figure 22 (left) illustrates the instruments of NISAR. The S-band SAR with a shorter wavelength is more sensitive to light vegetation than the L band, which penetrates leaves to reveal wavelength is more sensitive to light vegetation than the L band, which penetrates leaves to reveal core structures. Figure 22 (right) is a pictorial description of the mission’s versatility. One can easily core structures. Figure 22 (right) is a pictorial description of the mission’s versatility. One can easily assume that the operation of such spacecraft will be tightly scheduled to allocate its resources to vast assume that the operation of such spacecraft will be tightly scheduled to allocate its resources to vast areas for different purposes. Equatorial regions are especially difficult to observe frequently because areas for different purposes. Equatorial regions are especially difficult to observe frequently because ground swaths become sparser. These spatiotemporal gaps can be first remedied by small satellites ground swaths become sparser. These spatiotemporal gaps can be first remedied by small satellites that can be launched in multiples and may use non-Sun-synchronous orbits (inclined orbits) [125]. that can be launched in multiples and may use non-Sun-synchronous orbits (inclined orbits) [125]. Table8 takes NovaSAR as an example in which an assumed equatorial orbit significantly reduces the Table 8 takes NovaSAR as an example in which an assumed equatorial orbit significantly reduces the revisit time than a Sun-synchronous orbit. The resolution and the frequency bands of small-satellite revisit time than a Sun-synchronous orbit. The resolution and the frequency bands of small-satellite SAR are comparable to NISAR or Tandem-L, only falling behind in swath width. SAR are comparable to NISAR or Tandem-L, only falling behind in swath width.

Figure 22. NISAR spacecraft and mission concept: (left) Deployed configuration and internal subsystems includingFigure 22. 24 NISAR L-band spacecraft Tx/Rx modules and andmission 48 S-band concept: modules (left) (12Deployed per polarization). configuration (right and) Areas internal and topicssubsystems of interest including in India 24 andL-band neighboring Tx/Rx modules regions. an Source:d 48 S-band JPL, modules ISRO. (12 per polarization). (right) Areas and topics of interest in India and neighboring regions. Source: JPL, ISRO. Table 8. Comparison of NISAR, Tandem-L, and NovaSAR missions (~2018). Table 8. Comparison of NISAR, Tandem-L, and NovaSAR missions (~2018). Mission NISAR Tandem-L NovaSAR #Mission Sats ( ) 1 SSONISAR 2Tandem-L SSO 1 SSO NovaSAR3 SSO # Sats () Orbit→ 1 SSO 2 SSO 1 SSO EqO (15◦) 3 SSOEqO (15◦EqO) Orbit (inc) (98.4◦) (98.4◦) (97.5◦) EqO (15°) (97.5◦) (inc) (98.4°) (98.4°) (97.5°) (97.5°) (15°) Altitude 747 km 745 km 580 km ( )( )( ) ←  ←  ←  AltitudeLTAN 18:00 747 h km - 745 km 10:30 580 h km ( )( ( ) )(( ) ) ( ) ← ← ← RepeatLTAN cycle 12 day18:00 h 16 days - - 10:30 h - () -() - () RepeatRevisit cycle time 5–7 12 day day 3–4 16day days 1–3 day - 0.5–1.5 day - 0.5–1.5 day - 0.3 day - Band S, L L S ( )(0.5–1.5 )( ) Revisit time 5–7 day 3–4 day 1–3 day ← ←0.5–1.5 day ← 0.3 day Resolution 7 m (Az), 7 m, 6–30 m ( )(day )( ) ← ← ← Band 3–24 mS, (SR) L 1 m (Spot)L S ( )(() )(() ) () ← ← ← ResolutionSwath 240 7+ mkm (Az), 350 km 7 m, 20–150 6–30km m ( )( () )(() ) () ← ← ← 3–24 m (SR) 1 m (Spot) () () () 4.2. Sub-ConstellationSwath Formation 240 + km Flight 350 km 20–150 km () () ()

4.2. Sub-ConstellationFormation flying Formation schemes resembling Flight the TDX mission were also demonstrated by a few non-SAR missions involving small spacecraft: the PRISMA (Prototype Research Instruments and Space Mission technologyFormation Advancement) flying schemes mission, resembling consisting the TDX of a mi 150ssion kg satellitewere also and demonstrated a 40 kg satellite, by a few and non- the PROBA-3SAR missions mission involving consisting small of aspacecraft: 300 kg satellite the PRIS and aMA 200 (Prototype kg satellite Research [126–128]. Instruments Several advanced and Space SAR techniquesMission technology for biospheric Advancement) monitoring mission, benefit fromconsisting having of multiple a 150 kg satellites. satellite and Digital a 40 elevation kg satellite, models and ofthe ground PROBA-3 surfaces mission generated consisting by InSAR of a 300 and kg forestsatellit heightse and a obtained200 kg satellite by polarimetric [126–128]. InSAR Several (Pol-InSAR) advanced togetherSAR techniques yield the for biomass biospheric (forest) monitoring volume and benefit mass, whichfrom having are deliverables multiple ofsatellites. future SAR Digital missions elevation such asmodels Tandem-L of ground and BIOMASS surfaces generated as well as by TSX InSAR/TDX [and129, 130forest]. Representative heights obtained baseline by polarimetric requirements InSAR are summarized(Pol-InSAR) intogether Table9 foryield an the instance biomass of the (forest) Tandem-L volume mission and mass, [ 25]. Nowwhich that are Pol-InSAR deliverables was of enabled future SAR missions such as Tandem-L and BIOMASS as well as TSX/TDX [129,130]. Representative baseline requirements are summarized in Table 9 for an instance of the Tandem-L mission [25]. Now that Pol-InSAR was enabled in the TDX mission whose mass is slight over 1 metric ton, more reduction in mass could be attempted within the medium satellite (500–1000 kg) range; prior to TDX, Pol-InSAR was only feasible in large satellites such as ENVISAT (C-band, 8 ton) and ALOS (L-band,

Remote Sens. 2020, 12, 2546 21 of 31

Remotein the Sens. TDX 2020 mission, 12, x FOR whose PEER mass REVIEW is slight over 1 metric ton, more reduction in mass could be attempted21 of 31 within the medium satellite (500–1000 kg) range; prior to TDX, Pol-InSAR was only feasible in large 3satellites ton). The such large-to-medium-sized as ENVISAT (C-band, spacecraft 8 ton) andcould ALOS be supported (L-band, by 3 ton). a swarm The of large-to-medium-sized small spacecraft that canspacecraft only receive could radar be supported echoes (no by transmitter) a swarm of and small communicate spacecraft thatindirectly can only with receive ground radar stations echoes for command(no transmitter) and data and handling communicate through indirectly their withmaster ground spacecraft, stations as forenvisioned command in and a concept data handling called “mirror-SAR”through their master [131,132]. spacecraft, In support as envisioned of formation in a fl conceptying, drifting called “mirror-SAR”orbits are used [131 for, 132SAR]. tomography In support of (verticalformation forest flying, profile) drifting and orbits the teardrop are used forpatterns SAR tomography of a “Cobra” (vertical array or forest constellation profile) and might the teardropbe used forpatterns holographic of a “Cobra” SAR tomography array or constellation (full 3-D forest might structure) be used for [53,55]. holographic The desired SAR tomography satellite movement (full 3-D forforest SAR structure) tomography [53,55 and]. The holographic desired satellite SAR tomograp movementhy for are SAR shown tomography in Figure and 23 [25,133,134]. holographic SARThe Cobratomography constellation, are shown originally in Figure intended 23[ 25, 133for, 134telecommunications,]. The Cobra constellation, uses medium-Earth originally intended orbits but for smallertelecommunications, heights (with usesmore medium-Earth satellites) could orbits be a butpossibility smaller for heights SAR (withobservation more satellites) given the could low-cost be a driverspossibility today for SARin both observation satellite givenmanufacturing the low-cost and drivers launch today services. in both While satellite this manufacturingconcept uses two and ellipticallaunch services. orbits with While different this concept arguments uses two of ellipticalperigee orbitsto create with two diff erentsides argumentsof a teardrop of perigee pattern, to multitudescreate two sidesof adjacent of a teardrop circular pattern, orbits may multitudes also be ofused adjacent to create circular the circular orbits may formation, also be usedwhich to could create bethe viewed circular as formation, extensions which of TDX/TSW could be helix viewed orbits as extensions[135]. of TDX/TSW helix orbits [135].

TableTable 9. 9. Tandem-LTandem-L requirements requirements in biosphere monitoring.

ApplicationApplication Resolution Resolution (Global/Local) (Global/Local) Accuracy Accuracy Upper canopy height and change 50 m/30 m 10% error for height <2 m Upper canopy height and change 50 m/30 m 10% error for height < 2 m 3D forest structure and change 50 m/30 m - 3D forest structure and change 50 m/30 m - Forest biomass and change 100 m/50 m 20% error for biomass <100 ton/ha Forest biomass and change 100 m/50 m 20% error for biomass < 100 ton/ha AgriculturalAgricultural SAR SAR products products 40 40 m m - -

FigureFigure 23. 23. FormationFormation flight flight for for 3-D 3-D SAR techniques: ( (leftleft)) SAR SAR tomography. tomography. ( (middlemiddle)) Holographic SARSAR tomography. tomography. ( (rightright)) Teardrop Teardrop pattern in the Cobra array of satellites. 4.3. Novel Topics in Biosphere-Anthroposphere InterActions 4.3. Novel Topics in Biosphere-Anthroposphere InterActions Global forest/non-forest mapping and forest area/biomass estimation could be made both accurate Global forest/non-forest mapping and forest area/biomass estimation could be made both and cost-efficient in remote, underdeveloped areas if multi-band information is combined, which is already accurate and cost-efficient in remote, underdeveloped areas if multi-band information is combined, the case in agricultural applications [136–139]. Another potential research area where data fusion may be which is already the case in agricultural applications [136–139]. Another potential research area useful is vulnerability arising from biosphere-anthroposphere interactions. Previous disaster monitoring where data fusion may be useful is vulnerability arising from biosphere-anthroposphere interactions. projects concentrated on anthropospheric interactions mainly with geosphere (e.g., earthquakes or Previous disaster monitoring projects concentrated on anthropospheric interactions mainly with volcanoes) or hydrosphere (e.g., floods), but even without these catastrophic events, public health geosphere (e.g., earthquakes or volcanoes) or hydrosphere (e.g., floods), but even without these is being threatened by global climate change and associated infectious diseases [140]. For example, catastrophic events, public health is being threatened by global climate change and associated malaria transmission might be facilitated in tropical highlands in the future [141]. Development of infectious diseases [140]. For example, malaria transmission might be facilitated in tropical highlands early-warning systems against malaria and other vector-borne diseases was attempted using satellite in the future [141]. Development of early-warning systems against malaria and other vector-borne imagery such as Landsat’s Thematic Mapper sensor in visible and infrared wavelengths [30–32,142]. diseases was attempted using satellite imagery such as Landsat’s Thematic Mapper sensor in visible Soil moisture in croplands, wetlands, and flooded areas can be measured through and vegetation and infrared wavelengths [30–32,142]. Soil moisture in croplands, wetlands, and flooded areas can using SAR [143–146]. The idea of disease modeling and surveillance using satellites has been around be measured through clouds and vegetation using SAR [143–146]. The idea of disease modeling and since the late 1980s, whose implementation in multiple wavebands would be timely and worthwhile surveillance using satellites has been around since the late 1980s, whose implementation in multiple considering increased pandemic risks today [147,148]. Minisatellites, microsatellites, and picosatellites wavebands would be timely and worthwhile considering increased pandemic risks today [147,148]. Minisatellites, microsatellites, and picosatellites introduced in Section 3 may have their own contributions ranging from surface monitoring to precipitation mapping

Remote Sens. 2020, 12, 2546 22 of 31 introduced in Section3 may have their own contributions ranging from surface monitoring to precipitation mapping.

5. Discussion With the new potential applications discussed in Section4, the competitiveness of small satellite constellations is assessed. Table 10 shows the cost breakdown of small-satellite SAR missions. Both the cost per kilogram (1st column) and the satellite cost for each mission (3rd column) include the launch cost, whose proportion is given by percentage (4th column). The cost per satellite is similar between ICEYE and Capella X-SAR, so it can be regarded that the cost of further reducing satellite sizes seems to counterbalance the benefit of lower launch costs due to the reduced mass; in both ICEYE and Capella X-SAR missions, the second generation had a larger volume and mass than the first generation, which implies the limitations of over-downsizing. When it comes to the launch cost, it may be reduced by making use of rideshares, mass deployment, and/or reusable launch vehicles. Albeit its higher degree of freedom in launch options, small rockets are not economically competitive at the moment; Electron costs 5 million USD (MUSD) to launch a 150–225 kg payload to a 500 km Sun-synchronous orbit whilst SpaceX’s rideshare program takes 1 MUSD under similar conditions [149,150]. The operational cost may also be reduced by sharing the established ground station network such as KSAT or Amazon Web Service (AWS), the latter of which has open-price policies throughout the globe in the range of 10–20 USD per minute [151]. After all, cost reduction, which has motivated the transition from large SAR satellites to small ones, will continue to happen in multiple cost components.

Table 10. NovaSAR observation modes and 1-satellite/3-satellite revisit performance [41].

Cost/kg Sat Mass Sat Cost Launch Cost Ground Mission Launch Vehicle (kUSD) (kg) (MUSD) (%) Station ICEYE 82 85 7 42 , Electron KSAT SAR-Lupe 117 770 90 24 Kosmos DLR TSX/TDX 143 1230 117 20 Dnepr DLR NovaSAR 146 400 59 23 PSLV KSAT Capella 163 48 8 21 Falcon 9, PSLV, Electron AWS X-SAR Cosmo-SkyMed 214 1700 364 13 Soyuz KSAT

The performance and the performance per cost is not the scope of this paper, and it would suffice for now to point out that optical data and SAR data cannot be compared in parallel; in SAR data, the most valuable information lies in its phase, which does not exist in optical data at all [152]. This is because SAR data is produced from the complex signal domain in InSAR, polarimetric SAR, and tomographic SAR. Another unique feature is that SAR data may contain underground information, possessing capabilities to look through the ground surface as well as clouds [153]. New automated methods for data analysis, mostly based on artificial intelligence (AI), should take these SAR-specific characteristics into account such that we can take full advantage of such systems. Having relevant datasets is quintessential during the training of AI-based methods, which may be learning from scratch or transfer learning [154]. Once the developed algorithms are powered by computing infrastructures, near-real-time monitoring of global biosphere and change detection thereof would be possible with the existing ground station services that have shortened the lead time from data acquisition to customer deliveries on the order of 15 min to 30 min [155–158].

6. Conclusions In Earth remote sensing, it is often useful to understand the data generation flows from the very beginning, satellites in this case. The SAR instruments onboard the spaceborne platforms, in particular, have been following a relatively simple flight heritage dating back to Seasat and ERS satellites (Section1). New space missions represented by small satellites, however, are driving cost reduction Remote Sens. 2020, 12, 2546 23 of 31 and changing the design paradigm of space-based SAR (Section2)[ 158]. The deployment of several SAR constellations will ensue from the deployment experience of optical satellite constellations and, at the same time, will be closely followed by the deployment of “mega-constellations” by space-internet service providers. Therefore, it would be advisable for the users of satellite imagery data to understand the ever-increasing environmental complexity in the low-Earth orbits and its potential ramifications such as in-orbit collisions or electromagnetic interference (EMI). The constellation proposed by SpaceX, for example, will consist of 4425 satellites during Phase 1, operating in 10.7–12.7 GHz, 13.85–14.5 GHz, 17.8–18.6 GHz, 18.8–19.3 GHz, 27.5–29.1 GHz, and 29.5–30 GHz partially overlapping with the Ka band [159]. This paper reviewed some of the medium-to-large SAR platforms that were launched in constellations (Section3). These SAR constellations achieved technological maturity not only in the individual satellite design but also in the constellation management, as testified by ten years of successful operations of Cosmo-SkyMed [160]. Minisatellites such as NovaSAR-1 have driven the satellite size down to the extent of being able to launch multiple SAR satellites at once. After exploring the utmost miniaturization limits, design iterations for SAR microsatellites are still underway. The advent of big data from SAR satellites creates new opportunities in the field of biospheric monitoring (Sections4 and5).

Author Contributions: S.W.P.conceived the scope, surveyed SAR missions, and wrote overviews in corresponding sections; S.B. helped to survey SAR missions, drawing figures, and writing the section for SAR design principles; S.K. assisted in writing paragraphs regarding power electronics and storage; O.d.W. helped writing paragraphs for satellites orbits and constellations. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Acknowledgments: The first author appreciates helpful discussions with Keejoo Lee at the Korea Aerospace Research Institute. Conflicts of Interest: The authors declare no conflict of interest.

References

1. Crutzen, P.J. The “anthropocene”. J. Phys. IV (Proc.) 2002, 12, 1–5. [CrossRef] 2. Bae, S.; Levick, S.R.; Heidrich, L.; Magdon, P.; Leutner, B.F.; Wöllauer, S.; Serebryanyk, A.; Nauss, T.; Krzystek, P.; Gossner, M.M.; et al. Radar vision in the mapping of forest biodiversity from space. Nat. Commun. 2019, 10, 4757. [CrossRef][PubMed] 3. Kato, A.; Wakabayashi, H.; Hayakawa, Y.; Bradford, M.; Watanabe, M.; Yamaguchi, Y. Tropical forest disaster monitoring with multi-scale sensors from terrestrial laser, UAV, to satellite radar. In Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 23–28 July 2017; pp. 2883–2886. 4. Matese, A.; Toscano, P.; Di Gennaro, S.F.; Genesio, L.; Vaccari, F.P.; Primicerio, J.; Belli, C.; Zaldei, A.; Bianconi, R.; Gioli, B. Intercomparison of UAV, aircraft and satellite remote sensing platforms for precision viticulture. Remote Sens. 2015, 7, 2971–2990. [CrossRef] 5. Peral, E.; Im, E.; Wye, L.; Lee, S.; Tanelli, S.; Rahmat-Samii, Y.; Horst, S.; Hoffman, J.; Yun, S.-H.; Imken, T.; et al. Radar technologies for earth remote sensing from platforms. Proc. IEEE 2018, 106, 404–418. [CrossRef] 6. Marinan, A.D.; Hein, A.G.A.G.I.; Lee, Z.T.; Carlton, A.K.; Cahoy, K.; Milstein, A.B.; Shields, M.W.; DiLiberto, M.T.; Blackwell, W.J. Analysis of the Microsized Microwave Atmospheric Satellite (MicroMAS) Communications Anomaly. J. Small Satell. 2018, 7, 683–699. 7. Space Advisory Company. Potential Synthetic Aperture Radar Applications of Small Satellites. 2017. Available online: http://www.unoosa.org/documents/pdf/psa/activities/2017/SouthAfrica/slides/Presentation23.pdf (accessed on 18 April 2020). 8. Moreira, A.; Prats-Iraola, P.; Younis, M.; Krieger, G.; Hajnsek, I.; Papathanassiou, K.P. A tutorial on synthetic aperture radar. IEEE Geosci. Remote Sens. Mag. 2013, 1, 6–43. [CrossRef] 9. Lubin, D.; Massom, R. Polar Remote Sensing: Volume I: Atmosphere and Oceans; Springer Science & Business Media: Berlin/Heidelberg, Germany, 2006; p. 389. Remote Sens. 2020, 12, 2546 24 of 31

10. PCI Geomatics. KOMPSAT-5. 2015. Available online: https://www.pcigeomatics.com/geomatica-help/ references/gdb_r/KOMPSAT5.html (accessed on 26 July 2020). 11. ESA eoPortal, SIR-A (Shuttle Imaging Radar)/OSTA-1 Payload on STS-2 Mission. 2020. Available online: https://directory.eoportal.org/web/eoportal/satellite-missions/s/sir-a (accessed on 26 May 2020). 12. ESA. ERS Overview. 2020. Available online: https://www.esa.int/Applications/Observing_the_Earth/ERS_ overview (accessed on 26 May 2020). 13. Alaska Satellite Facility. ALOS Phased Array type L-band Synthetic Aperture Radar. 2020. Available online: https://asf.alaska.edu/data-sets/sar-data-sets/alos-palsar/alos-palsar-about/ (accessed on 23 June 2020). 14. Moore, J.W. OSTA-1: The Space Shuttle’s first scientific payload. In Proceedings of the 33rd IAF/IAC Congress, Paris, France, 27 September–2 October 1982. 15. Elachi, C.; Brown, W.E.; Cimino, J.B.; Dixon, T.; Evans, D.L.; Ford, J.P.; Saunders, R.S.; Breed, C.; Masursky, H.; McCauley, J.F.; et al. Shuttle Imaging Radar Experiment. Science 1982, 218, 996–1003. [CrossRef][PubMed] 16. Attema, E.P.W. The Active Microwave Instrument On-Board the ERS-1 Satellite. Proc. IEEE 1991, 79, 791–799. [CrossRef] 17. Klees, R.; Massonnet, D. Deformation measurements using SAR interferometry: Potential and limitations. Geologie en Mijnbouw 1998, 77, 161–176. [CrossRef] 18. Baghdadi, N.; Zribi, M. Microwave Remote Sensing of Land Surfaces: Techniques and Methods; Elsevier: Amsterdam, The Netherlands, 2016; p. 68. 19. Pepe, A.; Calò, F. A review of interferometric synthetic aperture RADAR (InSAR) multi-track approaches for the retrieval of Earth’s surface displacements. Appl. Sci. 2017, 7, 1264. [CrossRef] 20. Knight, P.G. (Ed.) Glacier Science and Environmental Change; John Wiley & Sons: Hoboken, NJ, USA, 2008. 21. Rizzoli, P.; Martone, M.; Gonzalez, C.; Wecklich, C.; Tridon, D.B.; Bräutigam, B.; Markus, B.; Schulze, D.; Fritz, T.; Huber, M.; et al. Generation and performance assessment of the global TanDEM-X digital elevation model. ISPRS J. Photogramm. 2017, 132, 119–139. [CrossRef] 22. Romeiser, R.; Johannessen, J.; Chapron, B.; Collard, F.; Kudryavtsev, V.; Runge, H.; Suchandt, S. Direct Surface Current Field Imaging from Space by along-Track InSAR and Conventional SAR. In from Space; Barale, V., Gower, J., Alberotanza, L., Eds.; Springer: Dordrecht, The Netherlands, 2010. 23. Roth, A.; Marschalk, U.; Winkler, K.; Schättler, B.; Huber, M.; Georg, I.; Künzer, C.; Dech, S. Ten years of experience with scientific TerraSAR-X data utilization. Remote Sens. 2018, 10, 1170. [CrossRef] 24. Young, N. Applications of Interferometric Synthetic Aperture Radar (InSAR): A Small Research Investigation. 2018. Available online: https://www.researchgate.net/publication/328773243_Applications_of_Interferometric_ Synthetic_Aperture_Radar_InSAR_a_small_research_investigation (accessed on 23 June 2020). 25. DLR and Radar Institute. Research Results and Projects (2011–2017). 2017. Available online: https://www. dlr.de/hr/Portaldata/32/Resources/dokumente/broschueren/HR-Institute-Status-Report-2011-2017.pdf (accessed on 3 June 2020). 26. Chu, T.; Guo, X. Remote sensing techniques in monitoring post-fire effects and patterns of forest recovery in boreal forest regions: A review. Remote Sens. 2014, 6, 470–520. [CrossRef] 27. White, L.; Brisco, B.; Dabboor, M.; Schmitt, A.; Pratt, A. A collection of SAR methodologies for monitoring wetlands. Remote Sens. 2015, 7, 7615–7645. [CrossRef] 28. Xiong, S.; Muller, J.P.; Li, G. The application of ALOS/PALSAR InSAR to measure subsurface penetration depths in deserts. Remote Sens. 2017, 9, 638. [CrossRef] 29. Carreiras, J.M.; Quegan, S.; Le Toan, T.; Minh, D.H.T.; Saatchi, S.S.; Carvalhais, N.; Reichstein, M.; Scipal, K. Coverage of high biomass forests by the ESA BIOMASS mission under defense restrictions. Remote Sens. Environ. 2017, 196, 154–162. [CrossRef] 30. Adimi, F.; Soebiyanto, R.P.; Safi, N.; Kiang, R. Towards malaria risk prediction in Afghanistan using remote sensing. Malar. J. 2010, 9, 125. [CrossRef][PubMed] 31. Bøgh, C.; Lindsay, S.W.; Clarke, S.E.; Dean, A.; Jawara, M.; Pinder, M.; Thomas, C.J. High spatial resolution mapping of malaria transmission risk in the Gambia, west Africa, using LANDSAT TM satellite imagery. Am. J. Trop. Med. Hyg. 2007, 76, 875–881. [CrossRef] 32. Rogers, D.J.; Randolph, S.E.; Snow, R.W.; Hay, S.I. Satellite imagery in the study and forecast of malaria. Nature 2002, 415, 710–715. [CrossRef] 33. Braun, A. Radar Satellite Imagery for Humanitarian Response. Ph.D. Thesis, Universit of Tübingen, Tübingen, Germany, 2019. Remote Sens. 2020, 12, 2546 25 of 31

34. Paek, S.W. Reconfigurable Satellite Constellations for Geo-spatially Adaptive Earth-Observation Missions. Master’s Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 2012. 35. Tristancho, J. Implementation of a Femto-Satellite and a Mini-Launcher. Master’s Thesis, Universitat Politècnica de Catalunya, Barcelona, Spain, 2012. 36. Helvajian, H.; Janson, S.W. (Eds.) Small Satellites: Past, Present, and Future; Aerospace Press: El Segundo, CA, USA, 2008; ISBN 978-1-884989-22-3. 37. Deepak, R.A.; Twiggs, R.J. Thinking out of the box: Space science beyond the CubeSat. J. Small Satell. 2012, 1, 3–7. 38. Camps, A.; Golkar, A.; Gutierrez, A.; de Azua, J.R.; Munoz-Martin, J.F.; Fernandez, L.; Diez, C.; Aguilella, A.; Briatore, S.; Akhtyamov, R.; et al. FSSCAT, the 2017 Copernicus Masters’ “ESA Sentinel Small Satellite Challenge” Winner: A Federated Polar and Soil Moisture Tandem Mission Based on 6U . In Proceedings of the IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22–27 July 2018; IEEE: New York City, NY, USA, 2018; pp. 8285–8287. 39. Wright, R.; Nunes, M.; Lucey, P.; Flynn, L.; George, T.; Gunapala, S.; Ting, D.; Rafol, S.; Soibel, A.; Ferrari-Wong, C.; et al. HYTI: Thermal hyperspectral imaging from a CubeSat platform. Proc. SPIE 2019, 11131, 111310G. 40. Saito, H.; Hirokawa, J.; Tomura, T.; Akbar, P.R.; Pyne, B.; Tanaka, K.; Mita, M.; Kaneko, T.; Watanabe, H.L.; Ijichi, K. Development of Compact SAR Systems for Small Satellite. In Proceedings of the IGARSS 2019–2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 28 July–2 August 2019; IEEE: New York City, NY, USA, 2019; pp. 8440–8443. 41. Filippazzo, G.; Dinand, S. The Potential Impact of Small Satellite Radar Constellations On Traditional Space System. In Proceedings of the 5th Federated and Fractionated Satellite Systems Workshop, Ithaca, NY, USA, 2–3 November 2017. 42. Kim, Y.; Kim, M.; Han, B.; Kim, Y.; Shin, H. Optimum design of an SAR satellite constellation considering the revisit time using a genetic algorithm. Int. J. Aeronaut. Space Sci. 2017, 18, 334–343. [CrossRef] 43. NASA. NASA-ISRO SAR (NISAR) Mission Science Users’ Handbook. 2019. Available online: https: //nisar.jpl.nasa.gov/files/nisar/NISAR_Science_Users_Handbook.pdf (accessed on 3 June 2020). 44. Ocampo-Torres, F.J.; Gutiérrez-Nava, A.; Ponce, O.; Vicente-Vivas, E.; Pacheco, E. On the progress of the nano-satellite SAR based mission TOPMEX-9 and specification of potential applications advancing the Earth Observation Programme of the Mexican Space Agency. In Proceedings of the Conference on Space Optical Systems and Applications, Santa Monica, CA, USA, 11–13 May 2011; pp. 102–109. 45. Freeman, A. Design principles for smallsat SARs. In Proceedings of the 32nd Annual AIAA/USU Conference on Small Satellites, Logan, UT, USA, 4–9 August 2018. 46. Farquharson, G.; Woods, W.; Stringham, C.; Sankarambadi, N.; Riggi, L. The Capella Synthetic Aperture Radar Constellation. In Proceedings of the EUSAR 2018; 12th European Conference on Synthetic Aperture Radar, Aachen, Germany, 4–7 June 2018; VDE Verlag: Berlin, Germany, 2018; pp. 1–5. 47. Safy, M. Synthetic Aperture Radar for Small Satellite. Int. J. Innov. Technol. Eng. 2019, 9, 3435–3440. 48. Braun, H.M.; Knobloch, P.E. SAR on Small Satellites-Shown on the SAR-Lupe Example. In Proceedings of the International Radar Symposium, 2007 (IRS 2007), Cologne, Germany, 5–7 September 2007. 49. Zemann, J.L.; Nitschko, T.; Supper, L.; Konigsreiter, G. The Deployable Boom Assembly for SAR-Lupe. In Proceedings of the 28th ESA Antenna Workshop, Estec Noordwijk, The Netherlands, 31 May–3 June 2005. 50. Clark, R.M. The Technical Collection of Intelligence; CQ Press: Washington, DC, USA, 2010. 51. Soja, M.J. Modelling and Retrieval of Forest Parameters from Synthetic Aperture Radar Data; Chalmers University of Technology: Gothenburg, Sweden, 2014. 52. Paek, S.W.; de Weck, O.L.; Smith, M.W. Concurrent design optimization of Earth observation satellites and reconfigurable constellations. J. Brit. Interplanet. Soc. 2017, 70, 19–35. 53. Paek, S.W.; Kim, S.; de Weck, O.L. Optimization of reconfigurable satellite constellations using simulated annealing and genetic algorithm. Sensors 2019, 19, 765. [CrossRef][PubMed] 54. Covello, F.; Battazza, F.; Coletta, A.; Lopinto, E.; Fiorentino, C.; Pietranera, L.; Valentni, G.; Zoffoli, S. COSMO-SkyMed an existing opportunity for observing the Earth. J. Geodyn. 2010, 49, 171–180. [CrossRef] 55. Paek, S.W.; Kim, S.; Kronig, L.G.; de Weck, O.L. Sun-synchronous repeat ground tracks and other useful orbits for future space missions. Aeronaut. J. 2020, 124, 917–939. [CrossRef] Remote Sens. 2020, 12, 2546 26 of 31

56. Candela, L.; Caltagirone, F. Cosmo-SkyMed: Mission Definition, Main Application and Products. In Proceedings of the ESA POLinSAR Workshop, Frascati, Italy, 14–16 January 2003; ESA Publications Division: Noordwijk, The Netherlands, 2003. 57. Csizmar, A.; Richards, L.; Scorzafava, E.; Daprati, G.; Perrone, G. COSMO-SkyMed, First Lithium-Ion Battery for Space-based Radar. In Proceedings of the 7th European Space Power Conference, Stresa, Italy, 9–13 May 2005. 58. Troutman, J. SONY 18650 Hard Carbon Cell and SONY 18650 Hard Carbon Mandrel Cell. In Proceedings of the NASA Battery Workshop, 2011 NASA Battery Workshop, Huntsville, AL, USA, 15 November 2011. 59. Lombardo, P.A multichannel spaceborne radar for the COSMO-SkyMed satellite constellation. In Proceedings of the 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No. 04TH8720), Big Sky,MT, USA, 6–13 March 2004; IEEE: New York City, NY, USA, 2004; Volume 1. 60. Ochs, S.; Pitz, W. The terrasar-x and tandem-x satellites. In Proceedings of the 2007 3rd International Conference on Recent Advances in Space Technologies, Istanbul, , 14–16 June 2007; IEEE: New York City, NY, USA, 2007; pp. 294–298. 61. Krieger, G.; Zink, M.; Bachmann, M.; Bräutigam, B.; Schulze, D.; Martone, M.; Rizzoli, P.; Steinbrecher, U.; Antony, J.W.; De Zan, F.; et al. TanDEM-X: A radar interferometer with two formation-flying satellites. Acta . 2013, 89, 83–98. [CrossRef] 62. Moreira, A.; Krieger, G.; Hajnsek, I.; Hounam, D.; Werner, M.; Riegger, S.; Settelmeyer, E. TanDEM-X: A TerraSAR-X Add-On Satellite for Single-Pass SAR Interferometry. In Proceedings of the IGARSS 2004, Anchorage, AK, USA, 20–24 September 2004. 63. Martone, M.; Rizzoli, P.; Wecklich, C.; Gonzalez, C.; Bueso-Bello, J.-L.; Valdo, P.; Schulze, D.; Zink, M.; Krieger, K.; Moreira, A. The Global Forest/Non-Forest Map from TanDEM-X Interferometric SAR Data. Remote Sens. Environ. 2018, 205, 352–373. [CrossRef] 64. Krieger, G.; Fiedler, H.; Moreira, A. Bi-and multistatic SAR: Potentials and challenges. Proc. EUSAR 2004, 34, 365–370. 65. Krieger, G.; Fiedler, H.; Houman, D.; Moreira, A. Analysis of system concepts for bi-and multi-static SAR missions. In Proceedings of the IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France, 21–25 July 2003; IEEE: New York City, NY, USA, 2003; Volume 2, pp. 770–772. 66. Gill, E.; Runge, H. Tight formation flying for an along-track SAR interferometer. Acta Astronaut. 2004, 55, 473–485. [CrossRef] 67. Krieger, G.; Hajnsek, I.; Papathanassiou, K.P.; Younis, M.; Moreira, A. Interferometric synthetic aperture radar (SAR) missions employing formation flying. Proc. IEEE 2010, 98, 816–843. [CrossRef] 68. Satellite Configuration for Interferometric and/or Tomographic Remote Sensing by Means of Synthetic Aperture Radar (SAR). U.S. Patent No 6,677,884, 13 January 2004. 69. DLR. Earth Observation Center. 2020. Available online: https://geoservice.dlr.de/web/maps/tdmforest (accessed on 3 June 2020). 70. ETH Zurich. Chair of Earth Observation and Remote Sensing. 2020. Available online: https://eo.ifu.ethz.ch/ forschung/Techniques.html#par_textimage_2091550249 (accessed on 3 June 2020). 71. Ullmann, T.; Büdel, C.; Baumhauer, R. Characterization of arctic surface morphology by means of intermediated TanDEM-X digital elevation model data. Z. Geomorphol. 2017, 61, 3–25. [CrossRef] 72. Betbeder, J.; Rapinel, S.; Corpetti, T.; Pottier, E.; Corgne, S.; Hubert-Moy, L. Multitemporal classification of TerraSAR-X data for wetland vegetation mapping. J. Appl. Remote Sens. 2014, 8, 083648. [CrossRef] 73. Lopez-Sanchez, J.M.; Ballester-Berman, J.D.; Hajnsek, I. First results of rice monitoring practices in Spain by means of time series of TerraSAR-X dual-pol images. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2010, 4, 412–422. [CrossRef] 74. Koppe, W.; Gnyp, M.L.; Hütt, C.; Yao, Y.; Miao, Y.; Chen, X.; Bareth, G. Rice monitoring with multi-temporal and dual-polarimetric TerraSAR-X data. Int. J. Appl. Earth Obs. 2013, 21, 568–576. [CrossRef] 75. Tebaldini, S.; Nagler, T.; Rott, H.; Heilig, A. Imaging the internal structure of an alpine glacier via L-band airborne SAR tomography. IEEE Trans. Geosci. Remote Sens. 2016, 54, 7197–7209. [CrossRef] 76. Buckreuss, S.; Zink, M. TerraSAR-X and TanDEM-X mission status. In Proceedings of the EUSAR 2016: 11th European Conference on Synthetic Aperture Radar, Hamburg, Germany, 6–9 June 2016; VDE: Berlin, Germany, 2016; pp. 1–6. Remote Sens. 2020, 12, 2546 27 of 31

77. Howell, E. Two Private Satellites Just Docked in Space in Historic First for Orbital Servicing. 2020. Available online: https://www.space.com/private-satellites-docking-success-northrop-grumman-mev-1.html (accessed on 24 July 2020). 78. De Weck, O. A Review of Satellite Constellation Reconfiguration and Its Applications. In Proceedings of the 10th International Workshop on Satellite Constellations & Formation Flying, Glasgow, UK, 16–19 July 2019. 79. Tian, W.; Bian, X.; Shao, Y.; Zhang, Z. On the detection of oil spill with China’s HJ-1C SAR image. Aquat. Procedia 2015, 3, 144–150. [CrossRef] 80. Guo, H.; Fu, W.; Liu, G. Scientific Satellite and Moon-Based Earth Observation for Global Change; Springer: Singapore, 2019; p. 423. 81. Observing Systems Capability Analysis and Review Tool. Satellite: HJ-1C. 2020. Available online: https: //www.wmo-sat.info/oscar-staging/satellites/view/171 (accessed on 15 June 2020). 82. Bird, R.; Whittaker, P.; Stern, B.; Angli, N.; Cohen, M.; Guida, R. NovaSAR-S: A low cost approach to SAR applications. In Proceedings of the Conference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), Tsukuba, Japan, 23–27 September 2013; IEEE: New York City, NY, USA, 2013; pp. 84–87. 83. Iervolino, P.; Guida, R.; Whittaker, P. NovaSAR-S and maritime surveillance. In Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium-IGARSS, Melbourne, VIC, Australia, 21–26 July 2013; IEEE: New York City, NY, USA, 2013; pp. 1282–1285. 84. Davies, P.; Whittaker, P.; Bird, R.; Gomes, L.; Stern, B.; Sweeting, M.; Cohen, M.; Hall, D. NovaSAR–Bringing Radar Capability to the Disaster Monitoring Constellation. In Proceedings of the 26th Annual USU Conference on Small Satellites, Logan, UT, USA, 13–16 August 2012. 85. Natale, A.; Guida, R.; Bird, R.; Whittaker, P.; Cohen, M.; Hall, D. Demonstration and analysis of the applications of S-band SAR. In Proceedings of the 2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), Seoul, Korea, 26–30 September 2011; IEEE: New York City, NY, USA, 2011; pp. 1–4. 86. Pauwels, V.; Walker, J.; Grimaldi, S.; Wright, A.; Li, Y. Improving Flood Forecast Skill Using Remote Sensing Data. 2019. Available online: https://www.bnhcrc.com.au/sites/default/files/managed/downloads/ improving_flood_forecast_skill_using_remote_sensing_data_annual_report_2018-2019_final.pdf (accessed on 20 July 2020). 87. Surrey Satellite Technology Ltd. SSTL Announces NovaSAR-1 Data Deal with the Philippines. 2019. Available online: https://www.sstl.co.uk/media-hub/latest-news/2019/sstl-announces-novasar-1-data-deal- with-the-philip (accessed on 20 July 2020). 88. Gunter’s Space Page. Ofeq 8, 10 (TECSAR 1, 2/TechSAR 1, 2). 2020. Available online: https://space.skyrocket. de/doc_sdat/techsar-1.htm (accessed on 15 June 2020). 89. Baddeley, A. Israel Exploits Space Technologies, Capabilities. Available online: https://www.afcea.org/ content/israel-exploits-space-technologies-capabilities (accessed on 20 July 2020). 90. Curiel, A.D.S.; Whittaker, P.; Bird, R.; Haslehurst, A.; Nejadi, P.; Victoria, I.; Cawthorne, A.; Underwood, C.; Sweeting, M. Synthetic Aperture Radar on a Nanosatellite-is it Possible? In Proceedings of the 12th IAA Symposium on Small Satellites for Earth Observation. International Academy of Astronautics (IAA), Berlin, Germany, 6–10 May 2019. 91. Imbriale, W.A.; Gao, S.S.; Boccia, L. Space Antenna Handbook; John Wiley & Sons: Hoboken, NJ, USA, 2012. 92. Sharay, Y.; Naftaly, U. TECSAR: Design considerations and programme status. IEE Proc.-Radar Sonar Navig. 2006, 153, 117–121. [CrossRef] 93. Jeong, S.Y.; Lee, S.Y.; Bae, M.J.; Cho, K.D. Configuration design of a deployable SAR antenna for space application and tool-kit development. Int. J. Aeronaut. Space 2014, 42, 683–691. 94. Wegner, P.M.; Ganley, J.; Maly, J.R. EELV secondary payload adapter (ESPA): Providing increased access to space. In Proceedings of the 2001 IEEE Aerospace Conference Proceedings (Cat. No. 01TH8542), Big Sky, MT, USA, 10–17 March 2001; 2011; Volume 5, pp. 2563–2568. 95. Caffrey, R. Using Rideshare to Launch CubeSats & ESPA S/C. In Proceedings of the 2nd Planetary CubeSat Science Symposium, Greenbelt, MD, USA, 26 September 2017. 96. Rosen, P.A.; Kumar, R. The NISAR Mission–An NASA/ISRO Space Partnership Supporting Global Research and Applications. In Proceedings of the 2019 URSI Asia-Pacific Radio Science Conference (AP-RASC), New Delhi, India, 9–15 March 2019; 2019; p. 1. Remote Sens. 2020, 12, 2546 28 of 31

97. Freeman, A.; Johnson, W.T.K.; Huneycutt, B.; Jordan, R.; Hensley, S.; Siqueira, P.; Curlander, J. The” Myth” of the minimum SAR antenna area constraint. In Proceedings of the IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS’99 (Cat. No. 99CH36293), Hamburg, Germany, 28 June–2 July 1999; IEEE: New York City, NY, USA, 1999; Volume 3, pp. 1770–1772. 98. Girard, R.; Plourde, P.; Séguin, G. The RADARSAT constellation payload design. In Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain, 23–28 July 2007; IEEE: New York City, NY, USA, 2007; pp. 1387–1392. 99. De Almeida, F.Q.; Younis, M.; Krieger, G.; Moreira, A. An Analytical Error Model for Spaceborne SAR Multichannel Azimuth Reconstruction. IEEE Geosci. Remote S. 2017, 15, 853–857. [CrossRef] 100. Akbar, P.R.; Sumantyo, J.T.S.; Saito, H. Design of synthetic aperture radar onboard small satellite. SANE 2012, 112, 135–140. 101. Saito, H.; Pyne, B.; Tanaka, K.; Mita, M.; Kaneko, T.; Hirokawa, J.; Tomura, T.; Watanabe, H.; Akbar, P.R.; Ijichi, K. Proto-Flight Model of SAR for 100kg class Small Satellite. In Proceedings of the 33rd Annual AIAA/USU Conference on Small Satellites, Logan, UT, USA, 3–8 August 2019. 102. Pyne, B.; Ravindra, V.; Saito, H. An improved pulse repetition frequency selection scheme for synthetic aperture radar. In Proceedings of the 2015 European Radar Conference (EuRAD), Paris, France, 9–11 September 2015; IEEE: New York City, NY, USA, 2015; pp. 257–260. 103. Pyne, B.; Akbar, P.; Saito, H.; Zhang, M.; Hirokawa, J.; Ando, M. Design of a center-feed waveguide feeder for wideband rectangular parallel-plate slot-array antenna on-board space-borne X-band SAR system. In Proceedings of the 2016 46th European Microwave Conference (EuMC), London, UK, 4–6 October 2016; IEEE: New York City, NY, USA, 2016; pp. 1533–1536. 104. Pyne, B.; Akbar, P.R.; Ravindra, V.; Saito, H.; Hirokawa, J.; Fukami, T. Slot-Array Antenna Feeder Network for Space-Borne X-Band Synthetic Aperture Radar. IEEE Trans. Antennas Propag. 2018, 66, 3463–3474. [CrossRef] 105. Hirako, K.; Shirasaka, S.; Obata, T.; Nakasuka, S.; Saito, H.; Nakamura, S.; Tohara, T. Development of small satellite for X-Band compact synthetic aperture radar. J. Phys. Conf. Ser. 2018, 1130, 012013. [CrossRef] 106. Peral, E.; Tanelli, S.; Statham, S.; Joshi, S.; Imken, T.; Price, D.; Sauer, J.; Chahat, N.; Williams, A. RainCube: The first ever radar measurements from a CubeSat in space. J. Appl. Remote Sens. 2019, 13, 032504. [CrossRef] 107. Peral, E.; Imken, T.; Sauder, J.; Statham, S.; Tanelli, S.; Price, D.; Chahat, N.; Williams, A. RainCube, a Ka-Band Precipitation Radar in a 6U CubeSat. In Proceedings of the 31st Annual AIAA/USU Conference on Small Satellites, Logan, UT, USA, 5–10 August 2017. 108. JPL/Caltech. Radar in a CubeSat (RainCube). 2020. Available online: https://www.jpl.nasa.gov/cubesat/ missions/raincube.php (accessed on 21 June 2020). 109. Sim, E. Technology trends in Newspace smallsatellite constellation in low-Earth orbits. Proc. Korean Soc. Aeronaut. Space Sci. 2018, 11, 322–323. (In Korean) 110. ICEYE. Historical Launch of ICEYE-X1 on India’s PSLV-C40 Rocket Sends First Ever under 100 kg SAR Satellite Into Orbit. 2018. Available online: https://www.iceye.com/press/press-releases/iceye-successfully- launches-worlds-first-sar-microsatellite-and-establishes-finlands-first-commercial-satellite (accessed on 15 June 2020). 111. Campbell, B.; Cheng, T.; Garas, V.; Mitchell, D. Summary of Current Ice Characterization Research: Norway/Russia/Europe. National Petroleum Council Study on Research to Facilitate Prudent Arctic Development. 2014. Available online: https://www.npcarcticreport.org/pdf/tp/55_Summary_of_Current_ Ice_Characterization_Research-Norway-Russia-Europe.pdf (accessed on 19 June 2020). 112. ICEYE. ICEYE SAR Product Guide. 2019. Available online: https://www.iceye.com/hubfs/Downloadables/ ICEYE-SAR-Product-Guide-2019.pdf (accessed on 19 June 2020). 113. Gunter’s Space Page. Harbinger. 2020. Available online: https://space.skyrocket.de/doc_sdat/harbinger.htm (accessed on 21 June 2020). 114. Kaljord, A. Earth Observation for Maritime Operations-Current Capabilities and Future Potential. 2017. Available online: http://www.norwep.com/content/download/31293/225975/version/1/file/KSAT_ (accessed on 27 May 2020). 115. Capella Space. How space is bringing you closer to earth. Available online: https://www.capellaspace.com/ (accessed on 15 July 2020). Remote Sens. 2020, 12, 2546 29 of 31

116. Stringham, C.; Farquharson, G.; Castelletti, D.; Quist, E.; Riggi, L.; Eddy, D.; Soenen, S. The Capella X-band SAR Constellation for Rapid Imaging. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 28 July–2 August 2019; IEEE: New York City, NY, USA, 2019; pp. 9248–9251. 117. Harris, M. Is Amazon’s Satellite Ground Station Service Ready for Primetime? 2019. Available online: https://spectrum. ieee.org/tech-talk/aerospace/satellites/meet-haras-and-maris-amazons-first-satellite-ground-stations (accessed on 20 July 2020). 118. Cahoy, K.; Blackwell, W.J.; Allen, G.; Bury, M.; Efromson, R.; Galbraith, C.; Hancock, T.; Leslie, V.; Osaretin, I.; Retherford, L.; et al. The MicroMAS CubeSat Mission. In Proceedings of the American Geophysical Union, Fall Meeting, San Francisco, CA, USA, 3–7 December 2012; p. SA13B-2162. 119. Fjørtoft, R.; Gaudin, J.M.; Pourthié, N.; Lalaurie, J.C.; Mallet, A.; Nouvel, J.F.; Martinot-Lagarde, J.; Oriot, H.; Borderies, P.; Luiz, C.; et al. KaRIn on SWOT: Characteristics of near-nadir Ka-band interferometric SAR imagery. IEEE Trans. Geosci. Remote Sens. 2013, 52, 2172–2185. [CrossRef] 120. Neeck, S.P.; Lindstrom, E.J.; Vaze, P.V.; Fu, L.-L. Surface Water and Ocean Topography (SWOT) Mission. In Proceedings of the SPIE Remote Sensing 2012, ‘Sensors, Systems, and Next-Generation Satellites,’ Edinburgh, Scotland, UK, 24–27 September 2012; Volume 8533, p. 85330G. 121. Alsdorf, D.E.; Mognard, N.M.; Lettenmaier, D.P. Hydrologic Science and Satellite Measurements of Surface Water. In Proceedings of the American Geophysical Union, Fall Meeting, San Francisco, CA, USA, 13–17 December 2010. 122. Ku, C.S.; Chang, P.C.; Chang, Y.L. Experimental Study of Polarized Radar Scattering from the Tree Canopy at the Ka-Band. Int. J. Antennas Propag. 2019, 2019, 4610713. [CrossRef] 123. Cappelletti, C.; Martinotti, G.; Graziani, F. UniCubeSat: A test for the Gravity-Gradient Solar Array Boom. In Proceedings of the 62nd International Astronautical Congress, Cape Town, South Africa, 3–7 October 2011. paper: IAC-11-B4–6B.12. 124. Space Applications Centre, ISRO. Overview of NISAR Mission and Airborne L&S SAR. 2020. Available online: https://vedas.sac.gov.in/vedas/downloads/ertd/SAR/L_1.pdf (accessed on 11 June 2020). 125. L’Abbate, M.; Germani, C.; Torre, A. Compact SAR and Micro Satellite solutions for Earth observation. In Proceedings of the 31st Space Symposium, Technical Track, Colorado Springs, CO, USA, 13 April 2015; pp. 1–17. 126. D’Amico, S.; Ardaens, J.S.; Larsson, R. Spaceborne autonomous formation-flying experiment on the PRISMA mission. J. Guid. Control Dyn. 2012, 35, 834–850. [CrossRef] 127. Tarabini Castellani, L.; Llorente, J.S.; Fernández Ibarz, J.M.; Ruiz, M.; Mestreau-Garreau, A.; Cropp, A.; Santovincenzo, A. PROBA-3 mission. Int. J. Space Sci. Eng. 2013, 1, 349–366. [CrossRef] 128. Ardaens, J.S.; D’Amico, S.; Cropp, A. GPS-based relative navigation for the Proba-3 formation flying mission. Acta Astronaut. 2013, 91, 341–355. [CrossRef] 129. Solberg, S.; Riegler, G.; Nonin, P. Estimating forest biomass from TerraSAR-X StripMap radargrammetry. IEEE Trans. Geosci. Remote Sens. 2015, 53, 154–161. [CrossRef] 130. Perko, R.; Raggam, H.; Deutscher, J.; Gutjahr, K.; Schardt, M. Forest assessment using high resolution SAR data in X-band. Remote Sens. 2011, 3, 792–815. [CrossRef] 131. Konecny, G. Small satellites–A tool for Earth observation? In Proceedings of the XXth ISPRS Congress, Commission, Istanbul, Turkey, 12–23 July 2004; Volume 4, pp. 12–23. 132. Janoth, J.; Jochum, M.; Petrat, L.; Knigge, T. High Resolution wide Swath–the Next Generation X-Band Mission. In Proceedings of the IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 28 July–2 August 2019; IEEE: New York City, NY, USA, 2019; pp. 3535–3537. 133. Draim, J.E.; Inciardi, R.; Cefola, P.; Proulx, R.; Carter, D. Demonstration of the cobra teardrop concept using two smallsats in 8-hour elliptical orbits. In Proceedings of the 15th Annual USU Conference on Small Satellites, Logan, UT, USA, 13–16 August 2001. 134. Draim, J.E.; Cefola, P.J.; Ernandes, K.J. Seamless handovers in cobra teardrop satellite arrays. Acta Astronaut. 2007, 61, 139–150. [CrossRef] 135. Paek, S.W.; Kronig, L.G.; Ivanov, A.B.; de Weck, O.L. Satellite constellation design algorithm for remote sensing of diurnal cycles phenomena. Adv. Space Res. 2018, 62, 2529–2550. [CrossRef] 136. Næsset, E.; Ørka, H.O.; Solberg, S.; Bollandsås, O.M.; Hansen, E.H.; Mauya, E.; Zahabu, E.; Malimbwi, R.; Chamuya, N.; Olsson, H.; et al. Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps: A comparison of estimated precision. Remote Sens. Environ. 2016, 175, 282–300. [CrossRef] Remote Sens. 2020, 12, 2546 30 of 31

137. Shimada, M.; Itoh, T.; Motooka, T.; Watanabe, M.; Shiraishi, T.; Thapa, R.; Lucas, R. New global forest/ non-forest maps from ALOS PALSAR data (2007–2010). Remote Sens. Environ. 2014, 155, 13–31. [CrossRef] 138. Baghdadi, N.N.; El Hajj, M.; Zribi, M.; Fayad, I. Coupling SAR C-band and optical data for soil moisture and leaf area index retrieval over irrigated grasslands. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2015, 9, 1229–1243. [CrossRef] 139. El Hajj, M.; Baghdadi, N.; Bazzi, H.; Zribi, M. Penetration analysis of SAR signals in the C and L bands for wheat, maize, and grasslands. Remote Sens. 2019, 11, 31. [CrossRef] 140. Shuman, E.K. Global climate change and infectious diseases. N. Engl. J. Med. 2010, 362, 1061–1063. [CrossRef] 141. Caminade, C.; Kovats, S.; Rocklov, J.; Tompkins, A.M.; Morse, A.P.; Colón-González, F.J.; Stenlund, H.; Martens, P.; Lloyd, S.J. Impact of climate change on global malaria distribution. Proc. Natl. Acad. Sci. USA 2014, 111, 3286–3291. [CrossRef][PubMed] 142. Kazansky, Y.; Wood, D.; Sutherlun, J. The current and potential role of satellite remote sensing in the campaign against malaria. Acta Astronaut. 2016, 121, 292–305. [CrossRef] 143. Beck, L.R.; Lobitz, B.M.; Wood, B.L. Remote sensing and human health: New sensors and new opportunities. Emerg. Infect. Dis. 2000, 6, 217. [CrossRef][PubMed] 144. Diuk-Wasser, M.A.; Dolo, G.; Bagayoko, M.; Sogoba, N.; Toure, M.B.; Moghaddam, M.; Manoukis, M.; Rian, S.; Traore, S.F.; Taylor, C.E. Patterns of irrigated rice growth and malaria vector breeding in Mali using multi-temporal ERS-2 synthetic aperture radar. Int. J. Remote Sens. 2006, 27, 535–548. [CrossRef][PubMed] 145. Catry, T.; Li, Z.; Roux, E.; Herbreteau, V.; Gurgel, H.; Mangeas, M.; Seyler, F.; Dessay, N. Wetlands and malaria in the Amazon: Guidelines for the use of synthetic aperture radar remote-sensing. Int. J. Environ. Res. 2018, 15, 468. [CrossRef] 146. Imhoff, M.L.; McCandless, S.W. Flood boundary delineation through clouds and vegetation using L-band space-borne radar: A potential new tool for disease vector control programs. Acta Astronaut. 1988, 17, 1003–1007. [CrossRef] 147. Ambrosia, V.G.; Linthicum, K.G.; Bailey, C.L.; Sebesta, P. Modelling Rift Valley fever (RVF) disease vector habitats using active and passive remote sensing systems. In Proceedings of the 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada, 10–14 July 1989; IEEE: New York City, NY, USA, 1989; Volume 5, pp. 2758–2760. 148. Lleo, M.M.; Lafaye, M.; Guell, A. Application of space technologies to the surveillance and modelling of waterborne diseases. Curr. Opin. Biotechnol. 2008, 19, 307–312. [CrossRef] 149. Mann, A. ’s Electron Rocket. 2019. Available online: https://www.space.com/electron-rocket.html (accessed on 19 July 2020). 150. Erwin, S. SpaceX Rideshare Program Putting Downward Pressure on Prices. 2020. Available online: https: //spacenews.com/spacex-rideshare-program-putting-downward-pressure-on-prices/ (accessed on 19 July 2020). 151. Amazon Web Services. AWS Ground Station Pricing. 2020. Available online: https://aws.amazon.com/ko/ ground-station/pricing/ (accessed on 21 July 2020). 152. Zhu, X.X.; Montazeri, S.; Ali, M.; Hua, Y.; Wang, Y.; Mou, L.; Shi, Y.; Xu, F.; Balmer, R. Deep Learning Meets SAR. IEEE Geosci. Remote Sens. Mag. 2020. in submitted. 153. Rotter, P.; Muron, W. Automatic Detection of Subsidence Troughs in SAR Interferograms Based on olutional Neural Networks. IEEE Geosci. Remote Sens. 2020.[CrossRef] 154. Soldin, R.J. SAR Target Recognition with Deep Learning. In Proceedings of the 2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), Washington, DC, USA, 9–11 October 2018; IEEE: New York City, NY, USA, 2018; pp. 1–8. 155. Ban, Y.; Zhang, P.; Nascetti, A.; Bevington, A.R.; Wulder, M.A. Near Real-Time Wildfire Progression Monitoring with Sentinel-1 SAR Time Series and Deep Learning. Sci. Rep. 2020, 10, 1–15. [CrossRef] 156. Tom, M.; Aguilar, R.; Imhof, P.; Leinss, S.; Baltsavias, E.; Schindler, K. Lake Ice Detection from Sentinel-1 SAR with Deep Learning. arXiv 2020, arXiv:2002.07040. [CrossRef] 157. ICEYE. Breaking the 15 Minutes Barrier from Acquisition to Delivery for SAR Imaging. 2019. Available online: https://www.iceye.com/press/press-releases/iceye-ksat-announce-ground-segment-15-minute-tasking- to-processing-sar-image-capabilities (accessed on 21 July 2020). 158. Lu, Z.; Dzurisin, D. InSAR imaging of Aleutian volcanoes. In InSAR Imaging of Aleutian Volcanoes; Springer: Berlin/Heidelberg, Germany, 2014; p. 377. Remote Sens. 2020, 12, 2546 31 of 31

159. Pyne, B.; Saito, H.; Ravindra, B. Extended Chirp Pulsed Radar (ECMPR) Scheme for MicroXSAR onboard 100 kg Micro-satellite. In Proceedings of the 15th Space Science Symposium, Sagamihara, Japan, 6–7 January 2015. 160. US Federal Communications Commission. FCC Authorizes SpaceX to Provide Broadband Satellite Services. 2018. Available online: https://www.fcc.gov/document/fcc-authorizes-spacex-provide-broadband-satellite- services (accessed on 23 June 2020).

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).