remote sensing
Article Insect Monitoring Radar: Maximizing Performance and Utility
V. Alistair Drake 1,2,* , Shane Hatty 1,3, Colin Symons 1,4 and Haikou Wang 5
1 School of Science, UNSW Canberra, The University of New South Wales, Canberra, ACT 2610, Australia; [email protected] (S.H.); [email protected] (C.S.) 2 Institute for Applied Ecology, University of Canberra, Canberra, ACT 2617, Australia 3 Now at PO Box 154, Lobethal, SA 5241, Australia 4 Now with Western Sydney University Penrith, Penrith, NSW 2751, Australia 5 Australian Plague Locust Commission, Canberra, ACT 2601, Australia; [email protected] * Correspondence: [email protected]
Received: 11 January 2020; Accepted: 5 February 2020; Published: 11 February 2020
Abstract: Autonomously-operating radars employing the ‘ZLC configuration’ have been providing long-term datasets of insect flight activity to heights of about 1 km since the late 1990s. A unit of this type operating in Australia has recently received a major upgrade. The aim of the project was to maximize the utility of the radar to entomologists and aeroecologists by providing larger and more continuous datasets and extending observations to 2.5 km. The upgrade was achieved primarily by incorporating modern digital technology, which provides much improved data-acquisition-and-control performance and data-archiving capacity; by implementing a more comprehensive observing protocol; and by replacing fixed electronic signal-acquisition gates with specially developed software that identifies insect echoes and applies a narrow moving gate that follows them. The upgraded version provides an approximately five-fold increase in hourly sample sizes, a doubling of the duration of observations (from 12 to 24 h per day) and a doubling of the height range over which observations are made. The design considerations (incentives and constraints) that informed the various subsystem implementations are identified, and the necessary compromises are discussed. Observations of the development of a layer echo during a migration by two different insect types are presented as a demonstration of the upgraded unit’s capabilities.
Keywords: radar; insect; migration; aeroecology; signal gating; ZLC configuration
1. Introduction Radars that are specifically designed for long-term observations of insects flying at heights up to around 1 km were first deployed around 1990 [1]. From the late 1990s, a design employing the ‘ZLC (Zenith-pointing Linear-polarized Conical scan) configuration’ [2], in which the beam incorporates both rotating linear polarization and a very narrow angle conical scan (sometimes termed ‘nutation’), has predominated. Known variously as IMRs (‘insect monitoring radars’ [2]) or VLRs (‘vertical-looking radars’ [3]), units of this type have been operated over extended (multiple-year) periods in Australia, China, Japan, and the UK. Long-term data from these radars have led to advances in the understanding of migratory behaviour and its ecological consequences (e.g., [4,5]) and have also provided support for operational pest forecasting [6]. Observations from small, purpose-built radars such as these complement the data on insect movement that are now becoming available from operational weather-surveillance radars (WSRs, e.g., [7]). The narrow beam, high range resolution, and short observing range of the IMRs and VLRs allow them to resolve individual insects, enabling the discrimination of different target types [8,9] and the examination of within-population variances
Remote Sens. 2020, 12, 596; doi:10.3390/rs12040596 www.mdpi.com/journal/remotesensing Remote Sens. 2020, 12, 596 2 of 20 of migration parameters (e.g., [10]). The relatively low capital and running costs of these units makeRemote them Sens. more 2020, 12 compatible, 596 with the modest budgets typical of entomological and aeroecological2 of 21 research programs. population variances of migration parameters (e.g., [10]). The relatively low capital and running costs The original IMR and VLR implementations were developed during the 1990s and incorporated of these units make them more compatible with the modest budgets typical of entomological and technologiesaeroecological that research were available programs. and affordable at that time. As subunits have aged and come to need repair orThe replacement, original IMR more and VLR modern implementations equipment haswere been developed introduced, during either the 1990s through and incorporated necessity—as supersededtechnologies components that were available became and unavailable—or affordable at that to take time. advantage As subunits of have improved aged and performance come to need and reliability.repair or In replacement, the case of the more IMRs modern operating equipment in Australia, has been opportunities introduced, provided either through by new data-acquisitionnecessity―as technologiessuperseded have components led to a became more general unavailable review―or of to the take systems’ advantage design of improved and operating performance protocols, and as wellreliability. as recognition In the case that of an the IMR’s IMRs eff operatingectiveness in as Australia, a facility opportunities for observing provided insect migrationby new data could‐ beacquisition considerably technologies increased. have Experience led to a more gained general through review analysing of the systems’ IMR data design from and over operating a decade (e.g.,protocols, [6,10,11 as]) alsowell informedas recognition this that review an IMR’s by indicating effectiveness circumstances as a facility for where observing larger insect datasets, migration or more continuouscould be considerably observation, increased. would likely Experience have enabled gained through additional analysing or stronger IMR data scientific from over inferences. a decade An upgraded(e.g., [6,10,11]) unit, designated also informed IMRU this review (‘IMR by Upgraded’), indicating circumstances was subsequently where developed larger datasets, and or deployed more continuous observation, would likely have enabled additional or stronger scientific inferences. An to Hay, New South Wales, Australia (34.5458◦S, 144.8663◦E), where it commenced observations in Augustupgraded 2017. unit, designated IMRU (‘IMR Upgraded’), was subsequently developed and deployed to Hay, New South Wales, Australia (34.5458°S, 144.8663°E), where it commenced observations in In this paper, the main features of the IMRU that distinguish it from its predecessors are outlined, August 2017. the methods used to enhance its performance are described, and example observations that illustrate In this paper, the main features of the IMRU that distinguish it from its predecessors are its capabilities are presented. The essential features of the ZLC configuration—vertical beam, rotating outlined, the methods used to enhance its performance are described, and example observations that polarization,illustrate its and capabilities narrow-angle are presented. scan—are The unchanged, essential features as is the of antenna the ZLC assembly configuration that implements―vertical thisbeam, [12] (ch.rotating 5). polarization, In its external and appearance, narrow‐angle therefore, scan―are theunchanged, unit resembles as is the anantenna IMR assembly (Figure1). that The IMRUimplements also continues this [12] to (ch. rely 5). on In an its X-band external transceiver appearance, that therefore, is derived the unit from resembles a commercial an IMR civil-marine (Figure radar1). The (BridgeMaster IMRU also continues E, Northrop to rely Grumman on an X‐band Sperry transceiver Marine, that New is derived Malden, from UK); a thiscommercial employs civil pulse‐ transmissionmarine radar (25 (BridgeMaster kW peak power) E, Northrop and operates Grumman non-coherently. Sperry Marine, The New innovations Malden, presented UK); this employs here relate to thepulse radar’s transmission operating (25 protocols kW peak andpower) the and initial operates processing, non‐coherently. both in hardware The innovations and software, presented of the echohere signals. relate Theto the extracted radar’s echooperating signals protocols differ little and fromthe initial those processing, from an IMR, both and in thehardware algorithm and for retrievingsoftware, trajectory of the echo and signals. target-character The extracted parameters echo signals from differ these little signals from [12 those] (ch. from 7) [ 13an] IMR, did not and require the modification.algorithm for The retrieving upgraded trajectory version and provides target‐character an approximately parameters five-fold from these increase signals in[12] hourly (ch. 7) sample [13] sizes,did a not doubling require of modification. the duration The of observations upgraded version (from provides 12 to 24 an h per approximately day), and a doublingfive‐fold increase of the height in rangehourly over sample which sizes, observations a doubling are of made. the duration of observations (from 12 to 24 h per day), and a doubling of the height range over which observations are made.
Figure 1. IMRU equipment cabin and antenna, Hay, New South Wales (NSW), April 2017. Figure 1. IMRU equipment cabin and antenna, Hay, New South Wales (NSW), April 2017.
TheThe IMRU IMRU may may represent represent the the limits limits of of what what non-coherentnon‐coherent radar radar technology technology—now―now superseded superseded in manyin many other other applications—can applications―can deliverdeliver for for entomological entomological observation. observation. However, However, much much of what of what is described here would be transferable to a ZLC unit that employs FMCW or pulse‐compression
Remote Sens. 2020, 12, 596 3 of 20 is described here would be transferable to a ZLC unit that employs FMCW or pulse-compression techniques (see, e.g., [12] (ch. 8)) or even to a fully-polarimetric vertical-beam design [14]. The paper discusses the design considerations behind each upgrade element, and this should assist the application of these methods in other contexts.
2. Materials and Methods A full specification of the IMRU is provided in Table1.
Table 1. Key IMRU design features and parameters.
Subsystem, Operation. Parameters, Features. Frequency/wavelength 9.4 GHz/3.2 cm (X-band). Transmitter Pulsed, 25 kW peak power (nominal), repetition frequency 960 Hz, pulse duration 0.05 µs (‘S-mode’), 0.25 µs (‘M-mode’). Receiver Non-coherent, logarithmic amplification; bandwidth ~20 MHz, minimum detectable signal 90 dBm. − Antenna Parabolic reflector, diameter 1.8 m, directed vertically; gain 43 dB; losses (radome, waveguide) ~3 dB (two way). Beam Circular pencil beam (full width at half maximum 1.1◦), Gaussian intensity pattern. Scan Narrow-angle conical, offset 0.24 beam-widths. 450 r.p.m. (7.5 Hz, period 0.133 s, alternating clockwise and anticlockwise at hourly intervals). Polarization Linear, turning synchronously with conical scan a; E-field aligned with offset direction. Video transformed into 5 to +5-V range and sampled at 60 or 120 MHz b over 0–9 µs (S-mode, 0–1350 m in range) or 8–17 µs (M-mode, Sampling (fast time) − 1200–2550 m); 540 or 1080 samples per pulse.
Sampling (slow time) 960 Hz (128 fast-time sequences per scan cycle). Observing protocol 15-min cycle comprising 3 S-mode and 1 M-mode observing periods, each of 3-min duration. Operation Continuous (“24/7”), fully automatic, with self-testing (multiple features) and autonomous recovery. a As polarization is axial, the modulation produced is double the scan rate, i.e., 15 Hz. b The 120-MHz rate provides greater precision and is preferred. The 60-MHz rate functions satisfactorily and allows for fast sampling on a second channel for system-integration testing.
2.1. System and Protocol Upgrades
2.1.1. “24/7” Observing and Data Storage Radars produce very large quantities of information, and in the 1990s, data-storage (and more particularly, archiving) limitations provided a constraint on the number of observations that it was practicable to record—at least when ZLC technology was still new and it seemed appropriate to retain the ‘raw’ (i.e., as-acquired) data. Accordingly, IMRs operated only during night-time hours—as the species of primary interest, the Australian plague locust Chortoicetes terminifera and a variety of noctuid moths, were known to be nocturnal migrants—and recorded for only about 30 min in every hour. VLRs, which immediately process the acquired data and record only small samples of the original signals, operate throughout the day and night [3]. This latter approach was adopted for the IMRU, which runs on a 15-min cycle: 12 min are allocated to observation, and the remainder are allocated to an initial processing stage (‘preprocessing’), writing the preprocessed data to disk, recording temperature and rain, backing the data up, and self-testing. Two cycles a day are sacrificed for (i) full processing of the day’s acquired data and (ii) a full system reboot; these are scheduled for, respectively, early morning and mid-afternoon—when experience suggests that transient phenomena of entomological or aeroecological interest are less likely to occur. Voucher files of 30 s of unprocessed signal data are also recorded four times a day to allow for a retrospective analysis of the radar’s performance; these files have also been used to develop and refine the preprocessing algorithm. With terabyte data drives now readily affordable and preprocessing essential (see below), data storage is no longer a constraint on operations.
2.1.2. Observing to 2.5 km IMRs, VLRs, and other ZLC implementations have so far employed pulse transmission with ‘short’ pulses (0.05 or 0.07 µs duration and 7.5 or 10.5 m effective length), and recorded echoes out to heights of around 1.3 km (‘S-mode’ [3,6]). While larger insects such as C. terminifera (mass ~400 mg for a migration-capable adult [9]) are detectable well above this, the successful analysis of the echo signals, leading to retrieval of all trajectory and target-character parameters, requires a strong echo that remains clear of the radar receiver’s electronic noise for several antenna-rotation cycles. For an IMR, the limiting Remote Sens. 2020, 12, 596 4 of 20 height has been empirically shown to be around 800 m for ‘small’ insects (~30 mg), 1000 m for ‘medium’ ones (~50 mg), and (by extrapolation) around 1700 km for ‘large’ ones (~250 mg) [15]. To enable the observation of migration at greater heights, the IMRU switches to ‘medium’-pulse (0.25 µs, 37.5 m) transmission for 3 min of each 15-min observing cycle. While in this ‘M-mode,’ data are acquired at ranges of 1200–2550 m. There is a 150-m deep overlap region with the S-mode observing range of 0–1350 m to allow for a comparison of performance of the two modes. A short pulse is preferable at lower heights because it reduces the likelihood of interference between the echoes from nearby targets; this is less of a problem above 1200 m, as insect densities are usually lower there. The divergence of the radar beam means that insect transit times, and therefore signal sequences, are longer in M-mode observations (because of the target’s greater height), and it seems plausible that this compensates for slower and less strong modulations due to the broader beam. The M-mode echoes have been found to satisfactorily process with the retrieval algorithm developed for the IMRs [13], so no modifications were needed.
2.1.3. Scan Speed and Direction To retrieve speed and direction, echo signals that extend over several rotation cycles of the narrow-angle scan are required. As the beam is quite narrow at low altitudes (8–10 m at 300 m [15]) 1 and insect speeds of ~10 m s− are commonplace at these heights, a scan rate of at least a few cycles per second is therefore needed. (A broader beam, produced by a lower-gain antenna, is not a viable alternative because at longer ranges, the horizontal resolution would be poor—leading to more frequent interference from nearby targets—and the echo signals would be weak.) The IMR used a scan rate of 5 Hz (300 rev/min). The scan also produced, via an angle encoder, a pulse train that was used to trigger the radar’s transmitter; with 256 pulses per cycle, a pulse repetition frequency (PRF) of 1280 Hz, which is just below the transmitter’s nominal maximum of 1300 Hz, was obtained. For the IMRU, the scan rate was increased to 7.5 Hz (450 rev/min), and the encoder output was reduced to 128 per cycle for a PRF of 960 Hz. The reduced average power output due to the lower PRF corresponds to a performance loss, assuming effective pulse-to-pulse averaging, of ~1 dB, but this is compensated for by 50% more cycles being available to the retrieval algorithm for estimating modulations. An increase in the scan rate to 10 Hz would eliminate the loss, but this has not been implemented because of concerns about the mechanical stability and integrity of the offset antenna feed—which already incorporates a counterweight to minimize centrifugal stress [12] (ch. 5). A question of current interest in insect migration studies that has been addressed mainly through ZLC-radar datasets, is the relationship between the insect’s orientation (or heading) and its direction of movement (or track). For some insect classes, biases to the left or the right have been observed [16]. As IMRs and VLRs operate with clockwise and anticlockwise rotation, respectively, concerns that such biases might be an artefact of the rotation direction could arise. A consideration of data-acquisition and parameter-retrieval processes do not support this, but doubts can be further reduced by simply reversing the rotation direction from time to time. The IMRU does this every hour, scanning clockwise on even hours and anticlockwise on odd. Modification of the retrieval algorithm has been minimized by treating all observations as clockwise until the end when, if rotation was in fact anticlockwise, the angle variables are transformed appropriately before being written to the output file.
2.1.4. Elimination of Stationary-Beam Observations The IMRs spent ~8 min in each hour observing with no scan rotation [17], as this was initially thought to be necessary to retrieve wingbeat frequencies (which have value for target identification). These observations had little general utility, as, without the scan, few other parameters could be retrieved. It was later determined that wingbeats could often be detected even in the highly variable scanning-beam signals [18], and these have proven much more valuable because they can be associated with other target-character parameters that are retrieved from the same echo. This leads to more confident assignments of individual echoes to different target classes—and, indeed, to more Remote Sens. 2020, 12, 596 5 of 20 sophisticated methods for recognizing those classes [8,9]. Accordingly, stationary beam observations have been eliminated from the IMRU’s operating protocol, and the time occupied by them has been reallocated to scanning-beam observations to improve the continuity and sample size of these. Stationary-beam observations require the radar’s PRF to be generated in an alternative way, and this facility was retained in the IMRU implementation so that this observation type could be reinstated; a practical option might be to assign the last 15-min cycle in each hour to stationary-beam operation. Wingbeat-frequency distributions that are produced with a stationary beam would be of better quality than those currently available, in which artefactual peaks at low harmonics of the scan-rotation rate (e.g., 15, 22.5, and 30 Hz) are often present.
2.1.5. Self-Test and Auto-Recovery To support their autonomous operation, IMRs incorporated a range of self-test features to monitor their performance and terminate operation in the event of a fault developing, as well as a mechanism for recovery from failures when these occured [19]. Remote access via a telephone link and modem enabled daily downloads of data summaries, and fault-finding and even reprogramming were possible without the need for a site visit. These facilities have largely been carried over to the IMRU, where they have been implemented with more modern technology and, in some instances, strengthened. Communication is now done via mobile telephony (using the 3G technology currently available at the radar site; Unimax MA-2025, Maxon Australia, Seven Hills, Australia) and a remote desktop connection (RDC; Microsoft Ltd., Redmond, WA, USA), which allows for full access to the radar’s control computer. All subunits, apart from the signal-acquisition system, are monitored and controlled via a USB connection to a multifunction card (USB6259, National Instruments, Austin, TX, USA). Self-testing extends to temperature (at 3 points—one inside the cabin, one outside in the cabin’s shade, and one on the motor under the antenna—with the termination of operation if any of these record a temperature exceeding 45 ◦C); mains power—supplied via an uninterruptible power supply (Powerware 9125, Eaton Corporation, Raleigh, NC, USA) to allow for a controlled termination in the event of a power cut; scan rotation rate; current drawn by the scan motor; scan internal alignment (to detect possible drive-belt slippage); PRF; and outputs from the transceiver’s BITE (‘built-in test equipment’) that include a tune indicator and the magnetron current. Transceiver performance is also monitored by means of a resonant cavity (65125V, Decca Marine Radar, London, UK) that is fed from the waveguide connecting the transceiver to the antenna. During tests, the tune voltage is varied, the value at which echo intensity is greatest is determined, and this value and the maximum intensity are recorded. When not in use, the cavity is switched out of tune with a solenoid so that no unwanted echo is produced. The transceiver’s auto-tune facility is activated for actual observations as it has proven reliable. Self-testing is undertaken during the 3 min in each 15-min cycle that is not used for observations and follows a schedule that ensures that each test occurs at least once every hour. Test outputs are recorded to a log file, along with details of the acquired signal data (times, file names, duration of data-acquisition period and of preprocessing, number of identified echoes, etc.), temperatures, and output from a rain detector. An inspection of the log file via RDC provides a means of determining whether the unit is functioning well and of diagnosing any faults. Operations are not terminated during rain, but the logged rain indications could be helpful when interpreting the observations. Other weather factors can be obtained from automatic weather stations (AWSs) operated at locations close to the radars by the Australian Bureau of Meteorology, so a dedicated AWS that is linked to the radar, as initially implemented with the IMRs [19], is no longer required. The scheduling system also manages the backing up of each day’s data to a removeable terabyte drive. If self-testing indicates a fault, the radar is closed down in a controlled way. A timer program then runs until 10 min before the following hour, when the main program is restarted. (The two programs are chained via a simple control file.) In some cases, normal operation resumes on the hour, and no more than 1 h of observations are lost. If the fault is persistent, this cycle continues until noticed via the Remote Sens. 2020, 12, 596 6 of 20
RDC link, when the main program can be disabled and the radar left dormant until the next servicing visit. Some self-test quantities vary considerably (e.g., motor current, according to temperature), and appropriate thresholds for termination have not yet been fully established. Self-test faults sometimes arise in the self-testing sensors or circuitry itself, and when this can be determined to be the case, it is usually straightforward to implement a ‘work-round’—i.e., to bypass the test with a minor software modification that can be undertaken remotely via RDC—and to quickly return the radar to operation. The IMRU undergoes an auto-recovery procedure each day at 16 h to bring it back into operation in the event of a fault that causes the control computer or the communication link to cease responding to commands. If the unit is operating normally, the scheduling software terminates observations, and the computer idles. An independent timer unit then cycles the power, causing the computer to reboot and commence its normal start-up protocol. A second timer cycles the power to the motor’s proprietary driver unit (TSD Single Axis; Baldor Electric Company, Fort Smith, AR, USA) as this also incorporates safety cut-outs that can be cleared in the same way. Recovery following an extended power outage occurs similarly; the radar restarts operation as soon as power becomes available.
2.2. Signal Acquisition and Preprocessing
2.2.1. Fast Data Acquisition The IMRs acquired radar echo signals via a bank of analogue-technology gated sample-and-hold circuits (Figure2) that were built specifically for this purpose. The circuits produced steady output voltages that could be digitized to reasonable precision (12 bits) at the low rates (kHz) that were achievable with the analogue-to-digital (A-to-D) conversion technology available in the 1990s. Each gate was paired with a low-pass filter that effectively produced a running average over a sequence of pulses, improving the signal-to-noise ratio (SNR) and eliminating any higher frequencies—but this process also introduced a delay. Digitization occurred at the filter outputs at 320 Hz, i.e., after every fourth pulse [17]. This system of data acquisition in ‘slow time’ (in the parlance of radar signal processing) produced a lot of useful data (e.g., [9,10]), but the fixed broad gates introduced some contamination (see below). The availability from the mid-2000s of affordable and fast A-to-D converters provided an opportunity to both eliminate a demanding in-house hardware build and to improve the radar’s data quality and coverage. With fast data acquisition, the analogue circuitry is eliminated and the radar’s ‘video’ output is directly converted into a sequence of digital values. For the non-coherent transceiver used in the IMRU, the video voltage is proportional to the logarithm of the intensity of the received signal. Echoes from targets at 2.55 km, the IMRU’s maximum observing range, take 17 µs to return to the radar. Sampling along the 0–17-µs interval (i.e., in ‘fast time’) needs to be sufficiently frequent to discern the numerous echoes that the radar is capable of resolving over this range (Figure2). Thus, A-to-D conversion at MHz frequencies is required. Echoes from a point target such as an insect have a nominal width of 0.05 µs when the IMRU is operating in S-mode, so a sampling frequency over 20 MHz ensures that echoes receive at least one digitization. However, while the transmitted pulse is approximately constant over its duration, the echo is rounded by the receiver’s matching 20-MHz bandwidth (see, e.g., [12] (ch. 3)). The peak of the rounded echo provides accurate—and consistent—measures of both the signal intensity (the peak height) and the target’s range (the time delay between transmission of the pulse and arrival of the echo). To obtain values for the peak, sampling at a rate significantly higher than 20 MHz (‘oversampling’) is needed. The IMRU uses a PCI 9820 converter (Adlink Technology, Taipei, Taiwan, China) which has maximum sampling rates of 120 MHz (single channel) or 60 MHz (two channels). The former, which was used in an earlier study [20], appears to be sufficient to locate the peak and determine its value by simply identifying the sample where the signal is strongest (Figure A1). The examples presented in this paper were acquired at 60 MHz, as the second channel was reallocated to a temporary system-integration test function (which does not need to be considered further here). At this Remote Sens. 2020, 12, 596 7 of 20 frequency, smoothing—as incorporated into the preprocessing, see below—or some other interpolative procedureRemote Sens. may 2020, be 12, needed596 to provide accurate peak determinations. 7 of 21
FigureFigure 2. 2.(a ()a Digitization) Digitization at at 6060 MHzMHz of an echo echo signal signal (a (a ‘pulse ‘pulse pair’—see pair’—see Appendix Appendix B) Bfrom) from the the IMRU IMRU atat Hay, Hay, NSW, NSW, on on 1 December,1 December, 2018 2018 at at 21.31 21.31 h.h. Key: mm—‘main—‘main bang’ bang’ (reverberation (reverberation from from transmitted transmitted pulse),pulse),c—ground c—ground clutter, clutter,n n—receiver—receiver noise, noise, and ii—insect echo. echo. (b (b) The) The gates gates used used in the in the earlier earlier Insect Insect MonitoringMonitoring Radars Radars (IMRs). (IMRs).
SamplingWith fast is data undertaken acquisition, for the each analogue pulse, circuitry from 0–9 is eliminatedµs when theand radarthe radar’s is operating ‘video’ output in S-mode is (Figuredirectly2) andconverted 8–17 µintos when a sequence in M-mode. of digital Each values. pulse For produces the non 1080‐coherent samples, transceiver 540 for used each in channel; the theIMRU, sampling the video interval voltage was is then proportional 0.167 µs, to corresponding the logarithm of to the 2.5 intensity m in range. of the With received a PRF signal. of 960 Echoes Hz, this leadsfrom to targets 1,036,800 at 2.55 samples km, the accumulating IMRU’s maximum each second observing and ~187 range, 10take6 over 17 s the to 3-minreturn durationto the radar. of each × data-acquisitionSampling along session. the 0–17 The‐s interval converter (i.e., has in ‘fast 14-bit time’) precision, needs to so be 2 bytes sufficiently (8-bit) frequent are needed to discern to store the each sample,numerous for aechoes total of that ~373 the Mbyte. radar is During capable acquisition, of resolving the over data this accumulate range (Figure on the 2). PCIThus, 9820 A‐to (which‐D fitsconversion into a bus at slot MHz of afrequencies standard PC-typeis required. microcomputer); Echoes from a atpoint the endtarget of such the 3-min as an session,insect have they a are transferrednominal width to the of PC’s 0.05 main s when memory the IMRU and immediately is operating subjected in S‐mode, to so preprocessing. a sampling frequency Only the over outputs from20 MHz preprocessing ensures that are echoes stored receive to archival at least file: one digitization. these vary in However, size but while typically the transmitted total ~300 pulse Mbyte is per approximately constant over its duration, the echo is rounded by the receiver’s matching 20‐MHz day, to which ~200 Mbyte has to be added for the voucher files for a total of ~200 Gbyte per year. bandwidth (see, e.g., [12] (ch. 3)). The peak of the rounded echo provides accurate―and This quantity of data is practicable to retain on a terabyte storage device that can be exchanged and consistent―measures of both the signal intensity (the peak height) and the target’s range (the time returned to the base laboratory during servicing visits. Full processing has not yet been implemented delay between transmission of the pulse and arrival of the echo). To obtain values for the peak, on a production basis, but it is envisaged that daily summaries will be produced for downloading via sampling at a rate significantly higher than 20 MHz (‘oversampling’) is needed. The IMRU uses a PCI RDC,9820 while converter the more (Adlink detailed Technology, results thatTaipei, are Taiwan, needed forChina) scientific which analyses has maximum will be sampling accumulated rates on of the terabyte120 MHz storage. (single channel) or 60 MHz (two channels). The former, which was used in an earlier study [20], appears to be sufficient to locate the peak and determine its value by simply identifying the 2.2.2. Video Amplifier sample where the signal is strongest (Figure A1). The examples presented in this paper were acquired at Both60 MHz, the as video the andsecond the channel trigger outputswas reallocated from the to transceiver a temporary are system mismatched‐integration for the test inputs function of the PCI(which 9820, does and annot interface need to be unit considered had to therefore further here). be built. At this Both frequency, voltage ranges smoothing and― impedancesas incorporated (75 and 50intoΩ) needthe preprocessing, changing. The see video below enters―or some as a other negative-going interpolative signal procedure of amplitude may be needed ~1 V. Toto provide match this wellaccurate to the peak5 to determinations.+5 V input range of the A-to-D, the signal is inverted, amplified, and offset so that it − extendsSampling over the rangeis undertaken4 to +4 for V (Figure each pulse,2). This from allows 0–9 fors when the full the exploitation radar is operating of the 14-bit in S‐ precisionmode (Figure 2) and 8–17 s− when in M‐mode. Each pulse produces 1080 samples, 540 for each channel. of the PCI 9820. In practice, echo signals from insects never approach saturation (at around +4 V), so With a PRF of 960 Hz, this leads to 1,036,800 samples accumulating each second and ~187106 over the dynamic range of the signal data from insect targets is typically about 12 bits (precision ~0.02%). the 3‐min duration of each data‐acquisition session. The converter has 14‐bit precision, so 2 bytes (8‐ The video circuitry maintains the 20-MHz bandwidth of the receiver and required careful design to bit) are needed to store each sample, for a total of ~373 Mbyte. During acquisition, the data avoid signal distortion and spontaneous oscillation. accumulate on the PCI 9820 (which fits into a bus slot of a standard PC‐type microcomputer); at the end of the 3‐min session, they are transferred to the PC’s main memory and immediately subjected to preprocessing. Only the outputs from preprocessing are stored to archival file: these vary in size but typically total ~300 Mbyte per day, to which ~200 Mbyte has to be added for the voucher files for a total of ~200 Gbyte per year. This quantity of data is practicable to retain on a terabyte storage device that can be exchanged and returned to the base laboratory during servicing visits. Full processing has
Remote Sens. 2020, 12, 596 8 of 20
2.2.3. Elimination of Fixed Gates It would have been straightforward to have reproduced the functioning of the IMR’s analogue gates (although not that of the accompanying low-pass filters) in software, using the 60-MHz (or 120-MHz) digitizations as input. However, gating—at least when implemented as fixed broad gates—has significant drawbacks (see AppendixA). A more sophisticated form of preprocessing was therefore developed in which echoes are first recognized and located, and then a narrow (and, if necessary, moving) gate is formed over the echo (in software) and used to extract the signal pulse by pulse (see below). The resulting sequences substitute well for the outputs of the IMR’s analogue gate circuits, though they differ from them in three respects: higher frequencies are not filtered out, there is no delay, and they are much less prone to the errors and distortions described in AppendixA. A great advantage of this approach is that echoes could be recognized and reconstructed throughout the entire 9-µs long sampling range, as the significant gaps that have to be left between fixed broad gates (see AppendixA) are eliminated. For the IMRU, this provides a 3-fold increase (over its IMR predecessors) in the number of echoes available for analysis in each 3-min sample. On an hourly basis, the increase is almost 5-fold, as there are more S-mode observing periods, and they last a little longer than the IMR ones. A more detailed description of the preprocessing algorithm that implements the moving gate is provided in AppendixB. The sample numbers of the peak position provide a precise measure of the time interval ∆t taken for the pulse to reach the target and return, and thus, by the usual radar relationship R = c∆t/2, of the range R. As the beam is vertical, the range corresponds to height h. Though the 0.05-µs pulse length indicates a range resolution of 7.5 m, the pulse-to-pulse scatter on the R values that are estimated from the sample numbers is much less than this. The explanation for this is that after rounding, the echo peak is well defined and the rounding occurs consistently from one pulse to the next. An investigation made when the sampling rate was 120 MHz showed that, after averaging over the 64 sample numbers obtained in each cycle (see AppendixB), remarkably high values for range precision of ~0.13 and ~0.2 m were obtained for the S and M modes respectively [20]. As beam transits typically last a few seconds, this precision, over ten or more cycles, allows target ascent (or descent) rates to be estimated, 2 in some cases with an uncertainty as low as 0.2 m s− . This has enabled phenomena not previously accessible with non-coherent radars to be observed [20]. With 60-MHz sampling, precision is reduced, but useful observations are still obtained.
2.2.4. Preprocessing Algorithm. The aim of preprocessing is to extract the data that contain useful information from the recorded echo sequences and to save only these to an archival file for later full processing. Depending on the number of targets present, preprocessing allows for 98–100% of the data recorded by the A-to-D converter to be discarded. Preprocessing needs to be rapid so that the loss of observing time is minimized and accurate, not least because discarded data cannot be recovered. The preprocessing algorithm developed for the IMRU has three principal functions: the identification of targets, the tracking of each target individually, and the use of the track to guide a narrow moving gate that extracts the target’s varying intensity. ‘Tracking’ here means determining the range of the target and following it as it varies (due to the target ascending or descending) from pulse to pulse (i.e., in slow time). Tracks need to be maintained even if the echo falls below the noise level for a fraction of each scan cycle, though when this fraction is large, the track can be abandoned (or not initiated). Using a narrow gate that moves eliminates almost all the limitations of fixed broad gates identified in AppendixA. When target densities are high, however, the extraction of individual echoes becomes impossible as targets overlap and interfere, so these echoes cannot be separated. To maintain some information output in these circumstances, the algorithm also calculates and saves average signal levels over a contiguous series of intervals spanning the full observation range. These averages can be drawn on to provide a general indication of insect activity and its variation with height, as well as to Remote Sens. 2020, 12, 596 9 of 20 avoid incorrectly inferring that insect numbers are low when a paucity of extracted echoes has in fact arisen through crowding. The algorithm progresses in 10 stages, the details of which are provided in AppendixB and the Supplementary Materials. A preliminary data-compression stage reduces the 128 pulses from each antenna rotation cycle to 64 ‘pulse pairs’. Targets are then identified though a rather involved procedure that incorporates smoothing, peak-detection, and counting peak detections in each cycle (stages 2-8). The output from stage 8 is a series of ‘linkages,’ each of which associates the echo from a particular target from one cycle to the next. A linkage’s running-average position forms the track that guides the narrow moving gate used to recover the echo signal (stage 9). As with the broad gates discussed previously, the highest value within the gate’s window is selected. However, because the gate encompasses only the top of the rounded echo peak, there is no chance of its output transferring to a stronger nearby echo or of recording a point on the echo’s shoulder rather than its peak, as happens when a gate is fixed and broad (AppendixA). The procedure sometimes outputs concatenations of two or more echoes, and these are split in a final stage 10.
3. Results Four examples of IMRU observations of phenomena involving insects ascending and descending during migratory flight have been presented previously [20]. We present here, as a more general example of the IMRU’s capabilities, observations of a nocturnal migration in which a distinct layer concentration developed and later dissolved (Figure3). Such layers can form through a range of behavioural responses to a variety of environmental cues [12] (ch. 10). Determining the specific interactions of behaviour and atmospheric phenomena that have led to the formation of a layer remains challenging, especially for examples, such as this one, that form well above the surface, beyond the likelyRemote extent Sens. 2020 (at this, 12, 596 stage of the night) of the surface temperature inversion. 10 of 21
FigureFigure 3. Graphical3. Graphical representation representation ofof outputoutput from full processing processing of of 1 1min min of of IMRU IMRU S‐mode S-mode (pulse (pulse durationduration 0.05 0.05µs) observationss) observations at Hay,at Hay, NSW, NSW, on 29on November,29 November, 2019 2019 at 22.09 at 22.09 h AEST h AEST (UTC (UTC+10).+10). The The short linesshort through lines eachthrough open each circle open indicate circle theindicate target’s the alignment. target’s alignment. Only targets Only for targets which for all which parameters all couldparameters be retrieved could are be presented. retrieved are Observations presented. Observations below 300 m below were severely300 m were affected severely by ground affected clutter by andground have been clutter omitted. and have been omitted.
AnAn inspection inspection of Figureof Figure3 indicates 3 indicates that that the the layer layer was was located located at at around around 950 950 m m above above the the surface surface and wasand approximately was approximately 100 m deep.100 m Itdeep. comprised It comprised large large insects, insects, with with polarization-averaged polarization‐averaged ventral-aspect ventral‐ 2 2 radaraspect cross-sections radar cross‐sections (RCSs) a(RCSs)0 of about a0 of about 1 cm 1, correspondingcm , corresponding to masses to masses of of 100–300 100–300 mg mg [ 12[12]] (ch. (ch. 4). 4). Known migrant species in this mass range that are found in inland New South Wales (NSW) include a number of larger noctuid moths and smaller specimens of C. terminifera. The layer targets were moving towards the NNE at speeds of 15–20 m s–1. Alignments were more varied, but a NE/SW trend is evident. (ZLC radar observations determine the alignment of an insect’s body axis, i.e., an angle in the range 0–180º, but do not resolve whether the insect is heading towards or away from this direction. Simultaneous measurements, or estimates, of the wind at the height of each target are needed to overcome this limitation [10], which also exists for alternative, e.g., scanning, radar configurations [12] (ch. 7).) Both above the layer and immediately below it, there were few insects, but below ~750 m, insects were again present. However, many of these were smaller (RCSs 0.01‐ 0.1 cm2, masses 30‐100 mg), moving more slowly (10‐15 m s–1) and towards the N or NNW, and had more varied alignments. A height–time plot of the fully analysed echoes from all the 3‐min observation periods between 20.00 and 02.00 h (Figure 4) indicates that the layer formed around 21.15 h when a thinning of targets at ~900 m started to become evident. At 22.00 h, the layer started to rise, reaching ~1300 m at midnight (by which time M‐mode observations were needed to follow it) and becoming more clearly separated from the migration below. A histogram of target sizes a0 (Figure 5) suggests three populations that were separated by troughs at –6 and –20 dBsc. By partitioning the targets at these points, it becomes evident that the layer comprised only the ‘large’ types (a0 peaking at 0 dBsc). These were also present below the layer, which had dissipated by 01.00 h (after which the large targets were spread fairly evenly throughout the height range 500–2000 m). ‘Medium‐sized’ targets (a0 peaking at –13 dBsc) were mainly confined to the region below 800 m once the layer had formed. This simple interpretation must be treated with caution, as larger targets are detectable to greater heights than smaller ones, and the observation ceiling for the medium targets is around 1 km [15]. Nevertheless, medium targets were observed to 1100 m at 21.00 h but were almost absent from the layer between
Remote Sens. 2020, 12, 596 10 of 20
Known migrant species in this mass range that are found in inland New South Wales (NSW) include a number of larger noctuid moths and smaller specimens of C. terminifera. The layer targets were 1 moving towards the NNE at speeds of 15–20 m s− . Alignments were more varied, but a NE/SW trend is evident. (ZLC radar observations determine the alignment of an insect’s body axis, i.e., an angle in the range 0–180º, but do not resolve whether the insect is heading towards or away from this direction. Simultaneous measurements, or estimates, of the wind at the height of each target are needed to overcome this limitation [10], which also exists for alternative, e.g., scanning, radar configurations [12] (ch. 7).) Both above the layer and immediately below it, there were few insects, but below ~750 m, insects were again present. However, many of these were smaller (RCSs 0.01–0.1 cm2, 1 masses 30–100 mg), moving more slowly (10–15 m s− ) and towards the N or NNW, and had more varied alignments. A height–time plot of the fully analysed echoes from all the 3-min observation periods between 20.00 and 02.00 h (Figure4) indicates that the layer formed around 21.15 h when a thinning of targets at ~900 m started to become evident. At 22.00 h, the layer started to rise, reaching ~1300 m at midnight (by which time M-mode observations were needed to follow it) and becoming more clearly separated from the migration below. A histogram of target sizes a0 (Figure5) suggests three populations that were separated by troughs at 6 and 20 dBsc. By partitioning the targets at these points, it becomes − − evident that the layer comprised only the ‘large’ types (a0 peaking at 0 dBsc). These were also present below the layer, which had dissipated by 01.00 h (after which the large targets were spread fairly evenly throughout the height range 500–2000 m). ‘Medium-sized’ targets (a peaking at 13 dBsc) 0 − were mainly confined to the region below 800 m once the layer had formed. This simple interpretation must be treated with caution, as larger targets are detectable to greater heights than smaller ones, and the observation ceiling for the medium targets is around 1 km [15]. Nevertheless, medium targets were observedRemote Sens. to 2020 1100, 12 m, 596 at 21.00 h but were almost absent from the layer between 21.15 and 22.3011 h of when 21 it was at or below this height. Thus, it appears that the medium-sized insects did not accompany the large21.15 ones and into22.30 the h when layer. it was at or below this height. Thus, it appears that the medium‐sized insects
Figure 4. Height–time plot for IMRU observations at Hay, NSW, during part of the night of 29–30 Figure 4. Height–time plot for IMRU observations at Hay, NSW, during part of the night of 29–30 November, 2019. Dusk (end of civil twilight) was at 19.45 h. Targets with a radar cross-section (RCS) a0 November, 2019. Dusk2 (end of civil twilight) was at 19.45 h. Targets with a radar cross‐section (RCS) > 6 dBsc (0.25 cm ) shown in blue. Small targets (a0 < 20 dBsc) have been omitted for clarity; they a−0 > –6 dBsc (0.25 cm2) shown in blue. Small targets (a0 < –20− dBsc) have been omitted for clarity; they were detectable only to about 500 m. were detectable only to about 500 m.
Figure 5. Histogram of RCS a0 values for the target sample of Figure 4.
The shapes of the large targets fell into the ‘main cluster region’ (MCR; see [8]) of the shape‐ parameter (2, 4) plane, while those of the medium targets fell into both the MCR and an extension of it to lower 2 values (down to 2 = 0.3) (Figure 6). The large targets met the criteria for the ‘type‐D’ class recognized by Hao et al. [9]. Medium targets usually have shapes in the MCR, so many of those recorded here were typical examples of targets of that size; those with lower 2 values perhaps had less elongated bodies than is usual in nocturnal migrants. Type‐D and typical medium targets, if flying at night, can be tentatively identified as moths [9]. Wingbeat frequencies (not shown) were predominantly in the range of 20–40 Hz, which is consistent with the moth identification. Wingbeats, which cannot always be retrieved, were available for 63% of the large targets but only 27% of the medium targets. Remote Sens. 2020, 12, 596 11 of 21
21.15 and 22.30 h when it was at or below this height. Thus, it appears that the medium‐sized insects
Figure 4. Height–time plot for IMRU observations at Hay, NSW, during part of the night of 29–30 November, 2019. Dusk (end of civil twilight) was at 19.45 h. Targets with a radar cross‐section (RCS) 2 Remote Sens.a0 >2020 –6 dBsc, 12, 596 (0.25 cm ) shown in blue. Small targets (a0 < –20 dBsc) have been omitted for clarity; they 11 of 20 were detectable only to about 500 m.
Figure 5. Histogram of RCS a0 values for the target sample of Figure4. Figure 5. Histogram of RCS a0 values for the target sample of Figure 4. The shapes of the large targets fell into the ‘main cluster region’ (MCR; see [8]) of the The shapes of the large targets fell into the ‘main cluster region’ (MCR; see [8]) of the shape‐ shape-parameter (α , α ) plane, while those of the medium targets fell into both the MCR and parameter (2, 4) 2plane,4 while those of the medium targets fell into both the MCR and an extension an extension of it to lower α values (down to α = 0.3) (Figure6). The large targets met the criteria of it to lower 2 values (down2 to 2 = 0.3) (Figure2 6). The large targets met the criteria for the ‘type‐D’ forclass the ‘type-D’ recognized class by recognizedHao et al. [9]. by Medium Hao et targets al. [9]. usually Medium have targets shapes usually in the haveMCR, shapes so many in of the those MCR, so manyrecorded of here those were recorded typical here examples were of typical targets examples of that size; of targetsthose with of thatlower size; 2 values those perhaps with lower had α2 valuesless perhapselongated had bodies less than elongated is usual bodies in nocturnal than is migrants. usual in nocturnalType‐D and migrants. typical medium Type-D targets, and typical if mediumflying targets,at night, if can flying be attentatively night, can identified be tentatively as moths identified [9]. Wingbeat as moths frequencies [9]. Wingbeat (not frequenciesshown) were (not shown)predominantly were predominantly in the range in of the 20–40 range Hz, of which 20–40 is Hz,consistent which with is consistent the moth with identification. the moth Wingbeats, identification. Wingbeats,which cannot which always cannot be always retrieved, be retrieved, were available were availablefor 63% of for the 63% large of thetargets large but targets only 27% but onlyof the 27% ofRemote themedium medium Sens. targets.2020 targets., 12, 596 12 of 21
Figure 6. Scatter plots of shape parameters α and α for (a) the large and (b) the medium-sized targets Figure 6. Scatter plots of shape parameters 22 and 4 4for (a) the large and (b) the medium‐sized targets inin Figure Figure4. 4. The The curve curve indicates indicates the the boundary boundary of the the possible possible values values of of 2α and2 and 4. α4.
AnAn inspection inspection of graphicalof graphical outputs outputs like like those those in Figure in Figure3 showed 3 showed that the that direction the direction of the migrationof the changedmigration little changed during little the during first few the hours, first few but hours, the higher-flying but the higher insects‐flying were insects heading were heading more to more the NE afterto the midnight NE after and midnight eventually, and eventually, from about from 03.00 about h, to 03.00 the E.h, to During the E. thisDuring later this part later of part the night,of the the migrationnight, the of migration medium-sized of medium targets‐sized below targets 800 below m became 800 m increasinglybecame increasingly both thin both and thin slow, and though slow, it wasthough still directed it was still to directed the N. to the N.
4.4. Discussion Discussion TheThe IMRU IMRU described described here here representsrepresents an an attempt attempt to to extend extend the the basic basic ZLC ZLC-configuration‐configuration design, design, withwith its its use use of non-coherentof non‐coherent pulse pulse radar radar technology, technology, to its to limits.its limits. The The aim aim was was to maximize to maximize the amount the ofamount biologically of biologically useful data useful that this data radar that typethis radar can provide type can and provide to develop and to an develop observing an facilityobserving of real utilityfacility for of entomologists real utility for and entomologists aeroecologists. and aeroecologists. Two further considerations Two further considerations informed this informed approach. this First, it wasapproach. a relatively First, it achievable was a relatively objective achievable given the objective resources given available the resources (principally available the (principally existing IMR the units andexisting expertise IMR developed units and through expertise operating developed them, through maintaining operating them, them, and maintaining analysing their them, data); and and analysing their data); and second, biological analyses of IMR datasets had made evident that there second, biological analyses of IMR datasets had made evident that there were gaps in coverage that were gaps in coverage that could usefully be filled, data samples that were quite frequently too small, could usefully be filled, data samples that were quite frequently too small, and some indications of and some indications of data contamination. The rapid improvement in (affordable) data‐acquisition and control technology since the 1990s, when the IMRs were designed, removed many of the limitations on data gathering and storage that had constrained the earlier design. Many of the improvements described here could be adapted for use in future entomological radars that employ more advanced radar technology, such as FMCW, pulse compression, polarimetry, or the use of millimetric wavelengths. Incorporating some of them may make the difference between a clever technological achievement and a long‐term observing system that provides data that researchers can exploit. The IMRU has operated satisfactorily at Hay over two insect‐flight seasons. (Breaks in the observation series can mostly be attributed to faults developing in ageing subunits that were carried over from the IMRs.) Nevertheless, the specific parameters and thresholds mentioned here should be regarded as tentative: their optimal values have not yet been established. The present 15‐min observing cycle, with 3 S and 1 M periods, each of 3 min, may also be modified. There may be a case for extending M observations downwards in order to increase the height range over which medium‐ sized targets can be observed. Similarly, it may be worthwhile to re‐introduce stationary‐beam observations, as the retrieval rate for wingbeat frequencies from rotating‐polarization echoes is low for some target classes. The layer example presented here provides an instance in which both of these modifications might have been beneficial. However, any such extensions of the present protocol will decrease sample sizes and the continuity of the primary S‐ and M‐mode datasets, and M‐mode observations nearer the surface may be too affected by interference (due to the longer M pulses and the typically higher target densities lower down) to be useful. Another possible modification is a reduction of the antenna rotation rate to 270 r.p.m (4.5 Hz) and then averaging sets of four consecutive pulses rather than two. This would allow an increase in the PRF and provide a somewhat
Remote Sens. 2020, 12, 596 12 of 20 data contamination. The rapid improvement in (affordable) data-acquisition and control technology since the 1990s, when the IMRs were designed, removed many of the limitations on data gathering and storage that had constrained the earlier design. Many of the improvements described here could be adapted for use in future entomological radars that employ more advanced radar technology, such as FMCW, pulse compression, polarimetry, or the use of millimetric wavelengths. Incorporating some of them may make the difference between a clever technological achievement and a long-term observing system that provides data that researchers can exploit. The IMRU has operated satisfactorily at Hay over two insect-flight seasons. (Breaks in the observation series can mostly be attributed to faults developing in ageing subunits that were carried over from the IMRs.) Nevertheless, the specific parameters and thresholds mentioned here should be regarded as tentative: their optimal values have not yet been established. The present 15-min observing cycle, with 3 S and 1 M periods, each of 3 min, may also be modified. There may be a case for extending M observations downwards in order to increase the height range over which medium-sized targets can be observed. Similarly, it may be worthwhile to re-introduce stationary-beam observations, as the retrieval rate for wingbeat frequencies from rotating-polarization echoes is low for some target classes. The layer example presented here provides an instance in which both of these modifications might have been beneficial. However, any such extensions of the present protocol will decrease sample sizes and the continuity of the primary S- and M-mode datasets, and M-mode observations nearer the surface may be too affected by interference (due to the longer M pulses and the typically higher target densities lower down) to be useful. Another possible modification is a reduction of the antenna rotation rate to 270 r.p.m (4.5 Hz) and then averaging sets of four consecutive pulses rather than two. This would allow an increase in the PRF and provide a somewhat better SNR, but this would come at the cost of less frequent target-position fixes. As is usual in radar design and operation, priorities must be decided on, and compromises made accordingly. Modifications of these types require only changes to the operating software, and they could be remotely implemented via the communications link, perhaps only temporarily for a short-term trial. The ability of IMRs and VLRs to operate autonomously, and the accumulation of extended observation datasets from locations far from the operators’ base that this enables, greatly increases the utility of these units for both research and operational monitoring for pest management. If located within the coverage of a WSR, the detailed local information provided by the ZLC unit can be used to help interpret the observations of insect, bird, and bat movements over a much wider area that a high-power scanning radar can provide. A further possible application, foreshadowed nearly three decades ago [21], is the monitoring of general environmental health, as measured by insect numbers and their year-to-year variations. Here, the advantages of radar are that the monitoring process can be fully automated and that consistent and continuous measurements—in a relatively simple environment, the atmosphere, in which insects cannot hide—are provided. Specific identifications will not be achievable, and this will limit the technique’s capacity to estimate biodiversity; however, as the example presented here demonstrates, partitioning of the radar counts, especially by size, is possible, so a series of information outputs could still be produced. The recent application of ZLC-radar observations to estimation of ‘bioflows’—of pollinators, natural enemies, pollen, and nutrients [5]—illustrates the breadth of environmental-health issues that a radar-based monitoring network could address. Laser-based techniques also show promise in this role [22], but they have different capabilities and provide complementary rather than equivalent information; thus, the two technologies might be particularly effective if operated side-by-side.
5. Conclusions Now over two decades old, the basic ‘ZLC’ radar design remains competitive as a means of observing and quantifying insect migration. It can determine all key migration parameters: the number of migrants, height, direction, speed, alignment, target size, and either two or three additional characters indicative of target identity. From these, the height profile of migration intensity and the Remote Sens. 2020, 12, 596 13 of 20 overall migration rate (and its direction) can be derived. With its ability to detect and characterize individual insects, as well as its consequent ability to partition the migrant population into different classes, it complements weather surveillance radars: while the latter scan over a wide area, they can provide information only about mixed ensembles of migrants. One weakness, the inability to resolve the 180º orientation ambiguity from radar data alone, is also shared by alternative observing systems. The developments reported here show that the quality, continuity, and sample sizes of the data from a ZLC radar can be considerably improved over what is being produced by earlier implementations of this configuration. These improvements first arise through the adoption of modern digital technology for data acquisition, control, and storage; they secondly arise through the development of special software for operating the radar and extracting echo signals; and they thirdly arise through the use of the radar transceiver’s ‘medium pulse’ operating mode to double the height range over which observations are made. As the examples here and in the previous paper [20] demonstrate, the upgraded radar is effective at revealing and examining the varied transient phenomena of insect migration, even when these extend to heights of over 2 km. The radar’s capacity for accumulating long-term datasets at a modest cost suggests that it will similarly enable the development of insights into seasonal migration patterns and their inter-annual variations in response to ecological drivers. There also appears to be scope for a role in monitoring large-scale ecosystem health and its variation over decadal or even longer timescales.
Supplementary Materials: Software implementing the target-identification and signal extraction algorithm described in Section 2.2.4 and AppendixB is available online at http: //www.mdpi.com/2072-4292/12/4/596/s1. Author Contributions: Conceptualization, project administration, funding acquisition, resources, analysis, writing—original draft preparation, V.A.D.; methodology/hardware, V.A.D., S.H., C.S.; software, V.A.D., S.H., H.W.; validation/system testing, V.A.D., C.S., H.W.; data curation, V.A.D., H.W.; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded initially by Australian Research Council Linkage Grant LP0348025 and completed with internal funding from UNSW Canberra and the Australian Plague Locust Commission. Acknowledgments: IMRU development has been supported by UNSW Canberra technical and engineering staff. It built on earlier IMR subunit designs and implementations developed by former UNSW student I.T. Harman and workshop staff. The IMRU is accommodated on the Hay Field Station of UNSW Sydney. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Disclaimer: Mention of a commercial product does not constitute or imply endorsement. Products mentioned may no longer be available.
Appendix A
Problems Arising with Fixed Gates A conventional sample-and-hold gate is opened after a fixed delay—from the transmission of the pulse in the case of a pulse radar—and closed after a second, usually shorter, delay. The maximum signal appearing at the gate input while the gate is open is held at the gate output for a long enough duration for the held value to be recorded. Gates therefore operate in fast time (see 2.2.1) to enable recording in slow time. The gate duration needs to be kept short so that the range (height in the case of a vertical-beam unit) of the target that produces the held signal is known with reasonable precision, and the probability of multiple signals being present in the gate is low. Therefore, to cover a useful proportion of the range over which observations need to be made, a bank of gates is typically required. The former IMRs used 15 gates with durations of 0.167 µs (which corresponds to a range interval of 25 m) that were separated by gaps 0.333 µs (50 m) long (Figure1). These design choices were informed by a need for good range resolution, an awareness of some of the problems discussed in this Appendix, and concerns about costs and system-complexity issues that would arise with an even larger number of gates. Remote Sens. 2020, 12, 596 14 of 20
Apart from the delay to opening, which determines the range at which the signal being sampled originates, the only gate parameter to be chosen is the ‘width,’ i.e., the duration for which the gate remains open. To accurately record a peak, the gate needs to encompass it (Figure A1a). Peak widths are determined by the duration of the transmitted pulse and the bandwidth of the receiver. For a strong peak, smoothing by the limited bandwidth will broaden the peak, at its base, to at least twice the pulse durationRemote Sens. (Figure 2020, 12A1, 596a). This suggests a criterion for a minimum gate width of 2–4 the pulse15 duration. of 21 ×
FigureFigure A1. A1.Actions Actions of gates (grey) (grey) on on echo echo signals. signals. Signals Signals are extracts are extracts from Figure from Figure 2. (a) Strong2.( a )echo Strong echoencompassed encompassed by gate by gateof duration of duration 0.167 0.167s (25 µm).s (25 Key: m). p—width Key: p—width of transmitted of transmitted pulse (0.05 pulse s, 7.5 (0.05 m); µs, 7.5arrows—echo m); arrows—echo width width 3‐dB (0.26 3-dB V) (0.26 down V) downfrom peak from and peak approximately and approximately equal to equal the pulse to the width. pulse ( width.b) (b)Echo Echo just just below below gate. gate. Dashed Dashed rectangle rectangle indicates indicates a supposed a supposed preceding preceding and and immediately immediately adjacent adjacent gate.gate. (c )(c Pair) Pair of of echoes echoes encompassed encompassed by a gate of of duration duration 0.5 0.5 sµ s(75 (75 m). m). (d) ( dSame) Same as ( asc), ( cbut), but for forthe the pulse-pairpulse‐pair recorded recorded one-quarter one‐quarter of of aa cyclecycle (33 ms) ms) earlier, earlier, when when the the beam beam polarization polarization differed differed by 90º. by 90 º.
WithWith a fixeda fixed gate, gate, it it is is not, not, of of course,course certain, certain that that the the gate gate will will encompass encompass the the peak peak (Figure (Figure A1b). A1 b). TheThe gate gate will will still still record record the the maximum maximum signal, signal, but but it willit will arise arise from from the the echo’s echo’s sloping sloping rise rise or fallor fall phase ratherphase than rather from than its from peak, its andpeak, it and will it be will less be thanless than the the true true value. value. The The chance chance ofof this happening happening is greateris greater for narrowfor narrow gates gates than than for for broader broader ones, ones, but but givengiven the finite finite width width of of the the stronger stronger echoes, echoes, it it cannot be made negligible without broadening the gates to such an extent that useful range resolution cannot be made negligible without broadening the gates to such an extent that useful range resolution (100 m or less for IMRU observations) would be lost. There is evidence of this effect in analyses of (100 m or less for IMRU observations) would be lost. There is evidence of this effect in analyses of IMR IMR data: when echoes attributable to C. terminifera are numerous, a lower number of echoes with data: when echoes attributable to C. terminifera are numerous, a lower number of echoes with similar similar shape parameters [8] and wingbeat frequencies but smaller RCSs are often also present (see shapee.g., parameters[9] (Figure 2b)). [8] andA further wingbeat problem frequencies with these but slope smaller recordings RCSs is are that often if the also target present is changing (see e.g., its [9] (Figurerange,2b)). the Arecorded further problemvalue will with change these rapidly slope recordingsas the sloping is that face if of the the target echo is moves changing relative its range, to the the recordedgate boundary. value will change rapidly as the sloping face of the echo moves relative to the gate boundary. TheThe recording recording of of slope slope values values introducesintroduces a a second second source source of of inaccuracy: inaccuracy: if gates if gates are aretoo tooclose, close, echoesechoes will will be be double double counted—once counted—once accurately and and a a second second time time with with too too low low a value a value (Figure (Figure A1b). A1 b). ToTo avoid avoid this, this, gates gates must must be be separated separated byby at least the the width width of of a a strong strong echo. echo. Thus, Thus, with with gating, gating, individualindividual data-acquisition data‐acquisition sessions sessions should should extend extend over over only only a proportion a proportion of theof the full full observation observation range. Fullrange. coverage Full coverage remains remains possible possible by stepping by stepping the gates the out gates over out a over sequence a sequence of sessions of sessions [15,17 [15,17],], but the numberbut the of number echoes of acquired echoes acquired (i.e., the (i.e., sample the sample size) will size) still will be still reduced. be reduced. Some of these undesirable effects will arise less frequently if the gates are made broader, but an additional problem then arises: there may be two or more echoes within the gate (Figure A1c). If the echoes are steady, exhibiting just a slow rise and fall, as occurs when stationary‐beam observations are made, the larger will be consistently recorded, the undesirable consequences will be limited to biases: echo numbers will be underestimated at higher densities, and larger targets will be represented disproportionately in the samples. (If the rises and falls are not synchronous, the gate output will at some point switch from one target to the other; this is not a great problem because
Remote Sens. 2020, 12, 596 15 of 20
Some of these undesirable effects will arise less frequently if the gates are made broader, but an additional problem then arises: there may be two or more echoes within the gate (Figure A1c). If the echoes are steady, exhibiting just a slow rise and fall, as occurs when stationary-beam observations are made, the larger will be consistently recorded, the undesirable consequences will be limited to biases: echo numbers will be underestimated at higher densities, and larger targets will be represented disproportionately in the samples. (If the rises and falls are not synchronous, the gate output will at some point switch from one target to the other; this is not a great problem because echoes that are concatenated in this way are quite easily split—see AppendixB.) However, the intensity of ZLC echoes from insects rapidly varies because of the rotating polarization and small-angle scan, typically peaking twice during each cycle. Unless two insects have the same orientation, the phases of these variations will differ; the maximum signal in the gate will then flip rapidly between the two echoes (Figure A1c,d), producing a mixed reconstructed signal. An inspection of IMR echoes that failed analysis indicates that some probably formed in this way (A.D., unpublished data). (Note that this mechanism is distinct from the electromagnetic interference that occurs—and likewise renders the echo unanalysable—when two targets differ in range by less than a pulse length.)
Appendix B
Preprocessing Procedure The preprocessing algorithm comprises 10 stages. Stage 1 performs a simple data compression. Digitization occurs for each pulse, of which there are 128 per antenna-rotation cycle. Angular resolution as high as this seems unnecessary, so pairs of consecutive pulses are summed to produce 64 values per cycle. Summing is undertaken directly with the binary values, after clearing the two unused top bits. An additional factor of 2 is incorporated into the conversion of the binary values to voltages, so the effect is one of simple averaging. As receiver noise will be uncorrelated from one pulse to the next (i.e., across slow time), SNR will be improved (by a factor of ~ √2). Target identification commences at stage 2, in which each pulse pair is smoothed by using a triangle function with a width close to that of the rounded echo: 5 samples wide for the S-mode (0.083 µs, or 13 m in range) and 17 (0.28 µs, 43 m) for the M-mode (Figure A2, which illustrates the process for an M-mode pulse-pair). These values are for 60 MHz sampling; for 120 MHz, the algorithm is identical, but these and other sample ranges are approximately doubled. The peaks in these smoothed sequences are identified in stage 3 by a simple procedure that identifies minima and maxima, ignoring fluctuations of 3 dB or less, and records peaks that rise 6 dB or more above the average level of the receiver noise (Figure A3). For S-mode echoes, these and all subsequent stages are applied only to ranges beyond the extent of the most severe ground clutter (90 m at Hay). Remote Sens. 2020, 12, 596 16 of 21
echoes that are concatenated in this way are quite easily split―see Appendix B.) However, the intensity of ZLC echoes from insects rapidly varies because of the rotating polarization and small‐ angle scan, typically peaking twice during each cycle. Unless two insects have the same orientation, the phases of these variations will differ; the maximum signal in the gate will then flip rapidly between the two echoes (Figure A1c,d), producing a mixed reconstructed signal. An inspection of IMR echoes that failed analysis indicates that some probably formed in this way (A.D., unpublished data). (Note that this mechanism is distinct from the electromagnetic interference that occurs―and likewise renders the echo unanalysable―when two targets differ in range by less than a pulse length.)
Appendix B.
Preprocessing Procedure The preprocessing algorithm comprises 10 stages. Stage 1 performs a simple data compression. Digitization occurs for each pulse, of which there are 128 per antenna‐rotation cycle. Angular resolution as high as this seems unnecessary, so pairs of consecutive pulses are summed to produce 64 values per cycle. Summing is undertaken directly with the binary values, after clearing the two unused top bits. An additional factor of 2 is incorporated into the conversion of the binary values to voltages, so the effect is one of simple averaging. As receiver noise will be uncorrelated from one pulse to the next (i.e., across slow time), SNR will be improved (by a factor of ~√2). Target identification commences at stage 2, in which each pulse pair is smoothed by using a triangle function with a width close to that of the rounded echo: 5 samples wide for the S‐mode (0.083 s, or 13 m in range) and 17 (0.28 s, 43 m) for the M‐mode (Figure A2, which illustrates the process for an M‐mode pulse‐pair). These values are for 60 MHz sampling; for 120 MHz, the algorithm is identical, but these and other sample ranges are approximately doubled. The peaks in these smoothed sequences are identified in stage 3 by a simple procedure that identifies minima and maxima, ignoring fluctuations of 3 dB or less, and records peaks that rise 6 dB or more above the Remote Sens. 2020, 12, 596 16 of 20 average level of the receiver noise (Figure A3). For S‐mode echoes, these and all subsequent stages are applied only to ranges beyond the extent of the most severe ground clutter (90 m at Hay).
FigureFigure A2. A2.Pulse Pulse pair pair from from the the IMRU IMRU at Hay,at Hay, NSW, NSW, on 1on December, 1 December, 2018 2018 at 21.41 at 21.41 h. ( ah.) Digitized(a) Digitized signal (slow-timesignal (slow average‐time average of two consecutiveof two consecutive M-mode M‐mode pulses). pulses). (b) Signal (b) Signal after after fast-time fast‐time smoothing smoothing with Remote Sens. 2020, 12, 596 17 of 21 17-samplewith 17‐sample wide triangle wide triangle function function (inset). (inset).
FigureFigure A3. A3.Waterfall Waterfall plot plot showing showing thethe 3232 smoothed pulse pulse pairs pairs from from the the first first half half of ofthe the cycle cycle that that included the pulse pair in Figure A2. Peaks identified in stage 3 are marked . The pulse pair shown in included the pulse pair in Figure A2. Peaks identified in stage 3 are marked ×. The pulse pair shown Figurein Figure A2 is A2 at theis at mid-point the mid‐point of the of the sequence. sequence.
TheThe next next two two stages stages consolidate consolidate allall thethe pulse-pairpulse‐pair peaks peaks within within a ascan scan cycle. cycle. As As the the cycles cycles last last 1 onlyonly 0.133 0.133 s, s, range range changes changes due due toto target ascent ascent or or descent descent (typically (typically at rates at rates of <4 of m< 4s–1 m [20]) s− will[20]) be will beless than than the the 2.5 2.5-m‐m distance distance between between samples. samples. Therefore, Therefore, the drift the drift of the of peaks the peaks within within a cycle a cyclewill be will bevery slight. slight. This This consolidation consolidation allows allows the the identity identity of ofan an echo echo to tobe bemaintained maintained even even if the if the echo echo intensityintensity falls falls below below noise noise for for some some parts parts ofof thethe cycle (Figure (Figure A3). A3). The The approach approach used used here here is to is count, to count, forfor each each ‘section’ ‘section’ of of the the observing observing range, range, thethe number of of pulse pulse-pairs‐pairs in in the the cycle cycle in inwhich which a peak a peak is is foundfound (stage (stage 4, 4, Figure Figure A4 A4).). A A section section consistsconsists of a single single sample sample interval interval for for S‐ S-observationsobservations and and three three adjacentadjacent sample sample intervals intervals for for M-observations M‐observations (with (with their their broaderbroader echoes), so so there there are are 540 540 sections sections for for S andS 180and for180 M. for In M. stage In stage 5, these 5, these counts counts are are smoothed smoothed both both in in range range (fast (fast time) time) andand overover cycles (i.e., (i.e., in in ‘very slow time,’ so termed as there are 64 slow‐time intervals in each cycle). The initial smoothing ‘very slow time,’ so termed as there are 64 slow-time intervals in each cycle). The initial smoothing is is in range, with a triangle function with a width of 5 sections (stage 5a, Figure A4b). A peak is in range, with a triangle function with a width of 5 sections (stage 5a, Figure A4b). A peak is assigned assigned to a single section of a pulse pair, with the adjacent sections empty. The function of this first to a single section of a pulse pair, with the adjacent sections empty. The function of this first smoothing smoothing is to integrate counts over adjacent sections in order to avoid the spuriously low values is tothat integrate arise when counts an echo over straddles adjacent a section sections boundary. in order The to avoid triangle the is spuriouslytherefore weighted low values to retain that the arise when0‐to an‐64 echo scale straddlesof the unsmoothed a section counts boundary. so that The comparison triangle iswith therefore a detection weighted threshold to retain (at stage the 6, 0-to-64 see below) is straightforward. The second smoothing is over 5 successive cycles (stage 5b, Figure A5), and the triangle function is weighted conventionally (i.e., to conserve the total count) for this, as the stage 5a output values will vary only slowly from cycle to cycle if a persistent echo is present.
Remote Sens. 2020, 12, 596 17 of 21
Figure A3. Waterfall plot showing the 32 smoothed pulse pairs from the first half of the cycle that included the pulse pair in Figure A2. Peaks identified in stage 3 are marked . The pulse pair shown in Figure A2 is at the mid‐point of the sequence.
The next two stages consolidate all the pulse‐pair peaks within a scan cycle. As the cycles last only 0.133 s, range changes due to target ascent or descent (typically at rates of <4 m s–1 [20]) will be less than the 2.5‐m distance between samples. Therefore, the drift of the peaks within a cycle will be very slight. This consolidation allows the identity of an echo to be maintained even if the echo intensity falls below noise for some parts of the cycle (Figure A3). The approach used here is to count, for each ‘section’ of the observing range, the number of pulse‐pairs in the cycle in which a peak is found (stage 4, Figure A4). A section consists of a single sample interval for S‐observations and three adjacent sample intervals for M‐observations (with their broader echoes), so there are 540 sections for S and 180 for M. In stage 5, these counts are smoothed both in range (fast time) and over cycles (i.e., in ‘very slow time,’ so termed as there are 64 slow‐time intervals in each cycle). The initial smoothing is in range, with a triangle function with a width of 5 sections (stage 5a, Figure A4b). A peak is Remoteassigned Sens. 2020 to a, 12 single, 596 section of a pulse pair, with the adjacent sections empty. The function of this first17 of 20 smoothing is to integrate counts over adjacent sections in order to avoid the spuriously low values that arise when an echo straddles a section boundary. The triangle is therefore weighted to retain the scale of the unsmoothed counts so that comparison with a detection threshold (at stage 6, see below) 0‐to‐64 scale of the unsmoothed counts so that comparison with a detection threshold (at stage 6, see is straightforward. The second smoothing is over 5 successive cycles (stage 5b, Figure A5), and the below) is straightforward. The second smoothing is over 5 successive cycles (stage 5b, Figure A5), triangle function is weighted conventionally (i.e., to conserve the total count) for this, as the stage 5a and the triangle function is weighted conventionally (i.e., to conserve the total count) for this, as the outputstage values 5a output will values vary onlywill vary slowly only from slowly cycle from to cyclecycle to if acycle persistent if a persistent echo is echo present. is present.
Remote Sens. 2020, 12, 596 18 of 21
Figure A4. Histograms of counts of peaks identified in individual pulse pairs of the cycle shown in Figure A4. Histograms of counts of peaks identified in individual pulse pairs of the cycle shown Figure A3 (terminated at 12 s). (a) Counts. (b) Counts after smoothing with a triangle function in Figure A3 (terminated at 12 µs). (a) Counts. (b) Counts after smoothing with a triangle function extending over 5 histogram bins and weighted to maintain the peak count. extending over 5 histogram bins and weighted to maintain the peak count.
Figure A5. Waterfall plot showing a sequence of 20 doubly-smoothed cycle counts including, at number Figure A5. Waterfall plot showing a sequence of 20 doubly‐smoothed cycle counts including, at 164, the cycle of Figure A4. Peaks identified in stage 6 are marked . number 164, the cycle of Figure A4. Peaks identified in stage 6 are marked× .
InIn stage stage 6, 6, peaks peaks in in fast-time fast‐time are are again again identified,identified, but but this this time time by by using using the the doubly doubly smoothed smoothed countscounts to to provide provide a a single single identification identification for for each each cycle cycle (Figure (Figure A5). A5 A threshold). A threshold of only of 8 counts, only 8 with counts, withfluctuations fluctuations of up of upto 6 to counts 6 counts ignored, ignored, was wasadopted adopted so that so weaker that weaker echoes echoes are detected are detected and the and thedurations durations (in (in very very slow slow time) time) of of stronger stronger ones ones are are maximized. maximized. These These peaks peaks are are largely largely free free of of fluctuationsfluctuations and and noise, noise, and and they they thus thus provide provide aa good basis for for identifying identifying and and tracking tracking targets. targets. This This occursoccurs in in stage stage 7, 7, which which links links peaks peaks in in sequencessequences of cycles. If If a a peak peak lies lies within within a 5 a‐section 5-section-wide‐wide windowwindow centred centred at at the the position position (the (the section section number)number) of of an an existing existing linkage, linkage, it itis isadded added to that to that linkage; linkage; if not,if not, a new a new linkage linkage is is generated. generated. Linkages Linkages are terminated as as soon soon as as no no stage stage 6 peak 6 peak is found is found within within thethe linkage’s linkage’s search search window. window. When When a a peak peak is is added added to to aa linkage,linkage, the linkage’s position, position, calculated calculated as as a runninga running average, average, is updated is updated and recorded.and recorded. A measure A measure of link of quality link quality is also is calculated also calculated and recorded; and it indicatesrecorded; how it indicates close the how new close peak the is, new in peak both is, range in both and range count, and to count, the linkage’s to the linkage’s previous previous values for thesevalues quantities for these (Figure quantities A6). (Figure When linkingA6). When is completed linking is completed (i.e., the final (i.e., cycle the final of the cycle 3-min of the dataset 3‐min has dataset has been processed), the accumulated linkages are reviewed, and very short ones (<4 cycles, the minimum length for which full analysis is possible) are culled (stage 8).
Remote Sens. 2020, 12, 596 18 of 20 been processed), the accumulated linkages are reviewed, and very short ones (<4 cycles, the minimum lengthRemote for Sens. which 2020, 12 full, 596 analysis is possible) are culled (stage 8). 19 of 21 Remote Sens. 2020, 12, 596 19 of 21
FigureFigure A6. A6.Linking Linking of of echo echo at at 9.8 9.8 µss inin Figure A5.A5.( (aa) )Smoothed Smoothed count count for for each each cycle; cycle; dashed dashed line line indicates threshold for inclusion in a linkage (8 out of the 64 pulse pairs). (b) Moving average linkage indicatesFigure A6. threshold Linking for of inclusion echo at 9.8 in a slinkage in Figure (8 out A5. of ( thea) Smoothed 64 pulse pairs). count ( bfor) Moving each cycle; average dashed linkage line positionpositionindicates (dashed (dashed threshold line)) line)) for used used inclusion to to guide guide in a the linkage narrow (8 out gate; gate; of in the in this this 64 example,pulse example, pairs). it remained it ( remainedb) Moving steady steady average at sector at linkage sector 37. 37. TheTheposition points points show(dashed show the line))the average average used position to positionguide for the eachfor narrow each cycle gate;cycle of the in of this smoothed the example, smoothed peaks it remained peaks for each for steady pulseeach atpulse pair, sector obtainedpair, 37. byobtained applicationThe points by applicationshow of the the narrow average of the gate narrow position in stage gate for 9. (in ceach) stage Quality cycle 9. (c of )of Quality links the smoothed between of links successive betweenpeaks for successive cycles,each pulse on cycles, a scalepair, of 0 (poor)onobtained a scale to 1 byof (good). 0application (poor) to 1 of(good). the narrow gate in stage 9. (c) Quality of links between successive cycles, on a scale of 0 (poor) to 1 (good). TheThe narrow narrow moving moving gate gate thatthat isis usedused to extract extract the the echo echo signal signal is iscentred centred on on the the linkage’s linkage’s running-averagerunningThe‐average narrow position position moving (stage (stage gate 9; that9; Figure Figure is used A6A6b).b). to The Theextract gate gate theis is 7 7 echosamples samples signal wide wide is forcentred for S‐observations S-observations on the linkage’s and and 13 13 (samples,(samples,running not‐average not sectors) sectors) position for for M-observations; M (stage‐observations; 9; Figure these A6b).these approximately approximatelyThe gate is 7 samples correspond correspond wide totofor thethe S‐observations distances at whichand which 13 an echoan(samples, fromecho from a not point a sectors) point target target for will M will‐ beobservations; be 3 dB 3 dB down down these from from approximately its its peak peak value.value. correspond The The gate gate positionto position the distances is reset is reset fromat fromwhich the the runningrunningan echo average fromaverage a atpoint at the the target start start ofwill of each each be 3 cycle, cycle,dB down and fromthen then itsthis this peak position position value. is isThe applied applied gate toposition toeach each of is of thereset the smoothed from smoothed the pulse-pairspulserunning‐pairs average (the (the stage stage at 2the 2 outputs, outputs, start of Figure eachFigure cycle, A2A2b)b) and in that then cycle. cycle. this Theposition The highest highest is applied value value within to within each the of the gate’s the gate’s smoothed window window is selectedispulse selected‐pairs (Figure (Figure (the stageA7 A7).). The2 The outputs, sequence sequence Figure ofof A2b) selections in that for for cycle. the the 64 The 64 pulse pulse-pairs highest‐pairs value in in each within each of ofthe the the cycles gate’s cycles included window included in theinis theselected linkage linkage (Figure forms forms theA7). the recovered The recovered sequence echo echo of signal signalselections for for that thatfor targetthe target 64 (Figurepulse (Figure‐pairs A8 A8).). in ThisThis each sequencesequence of the cycles is written included to to an an output file along with the start time, the number of cycles, the position at each cycle (and its outputin the file linkage along forms with thethe startrecovered time, echo the number signal for of that cycles, target the (Figure position A8). at This each sequence cycle (and is written its standard to standard deviation), and the link quality value for each cycle. deviation),an output and file the along link with quality the valuestart time, for each the cycle.number of cycles, the position at each cycle (and its standard deviation), and the link quality value for each cycle.
Figure A7. Smoothed pulse pair of Figure A2b (terminated at 12 s) with the track centre and gate Figure A7. Smoothed pulse pair of Figure A2b (terminated at 12 µs) with the track centre and gate windowFigure A7. (green) Smoothed for the pulse three pair identified of Figure echoes, A2b (terminated as well as theat 12 retrieved s) with peak the track positions centre (red) and andgate windowintensitieswindow (green) (green) (blue). for for the the three three identified identified echoes,echoes, as well as as the the retrieved retrieved peak peak positions positions (red) (red) and and intensitiesintensities (blue). (blue).
Remote Sens. 2020, 12, 596 19 of 20 Remote Sens. 2020, 12, 596 20 of 21
Figure A8. Echoes reconstructed with the narrow gate. Echoes are those at (a) 9.0 µs, (b) 9.8 µs and Figure A8. Echoes reconstructed with the narrow gate. Echoes are those at (a) 9.0 s, (b) 9.8 s and (c) (c) 11.2 µs in Figure A2. 11.2 s in Figure A2. The recovered signals need to be subjected to one further procedure before they can be passed to The recovered signals need to be subjected to one further procedure before they can be passed the parameter-retrieval algorithm. It has been found that linking (stage 7) sometimes concatenates two to the parameter‐retrieval algorithm. It has been found that linking (stage 7) sometimes concatenates ortwo more or nearby more nearby echoes, echoes, making making a switch a switch to a neighbouringto a neighbouring peak peak when when this this becomes becomes stronger stronger than thethan one the being one followed. being followed. Such sequences Such sequences usually usually exhibit exhibit more more than onethan rise-and-fall, one rise‐and‐ withfall, with a sudden a changesudden in change target position in target and position a decrease and a indecrease link quality in link at quality the transition at the transition point. In point. stage In 10, stage recovered 10, signalsrecovered are scanned signals are for thesescanned features for these and features split into and individual split into echoes.individual For echoes. programming For programming convenience, thisconvenience, procedure this has procedure been implemented has been implemented as part of the as full-processing part of the full‐processing algorithm, algorithm, of which of it formswhich the initialit forms stage. the initial stage.
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