Worldwide Availability of Maritime Medium-Frequency Radio Infrastructure for R-Mode-Supported Navigation

Journal of Marine Science and Engineering

Article Worldwide Availability of Maritime Medium-Frequency Radio Infrastructure for R-Mode-Supported Navigation

Paul Koch * and Stefan Gewies

German Aerospace Center (DLR), Institute of Communications and Navigation, Kalkhorstweg 53, 17235 Neustrelitz, Germany; [email protected] * Correspondence: [email protected]

Received: 10 January 2020; Accepted: 11 March 2020; Published: 18 March 2020

Abstract: The Ranging Mode (R-Mode), a maritime terrestrial navigation system under development, is a promising approach to increase the resilient provision of position, navigation and timing (PNT) information for bridge instruments, which rely on Global Navigation Satellite Systems (GNSS). The R-Mode utilizes existing maritime radio infrastructure such as marine radio beacons, which support maritime traffic with more reliable and accurate PNT data in areas with challenging conditions. This paper analyzes the potential service, which the R-Mode could provide to the mariner if worldwide radio beacons were upgraded to broadcast R-Mode signals. The authors assumed for this study that the R-Mode is available in the service area of the 357 operational radio beacons. The comparison with the maritime traffic, which was generated from a one-day worldwide Automatic Identification System (AIS) Class A dataset, showed that on average, 67% of ships would operate in a global R-Mode service area, 40% of ships would see at least three and 25% of ships would see at least four radio beacons at a time. This means that R-Mode would support 25% to 40% of all ships with position and 67% of all ships with PNT integrity information. The relatively high number of supported ships compared to the total radio beacon coverage of about 9% of the earth’s surface is caused by the good coverage of busy ports and areas such as the coast of China, North Sea and Baltic Sea. These numbers emphasize the importance of marine radio beacons for the R-Mode system.

Keywords: R-Mode; backup system; radio-beacon coverage; maritime traﬃc; AIS; medium frequency

1. Introduction Maritime traﬃc today is, with respect to navigation, tightly coupled on one or several Global Navigation Satellite Systems (GNSS). Many bridge systems use position, navigation and timing (PNT) information provided by GNSS receivers for their data processing, synchronization or information to the mariner. Unfortunately, GNSS signals are very weak when they arrive at the user so they are prone to interferences [1]. Furthermore, the ionosphere degrades the GNSS performance [2]. In order to provide reliable PNT information, additional sensors have to be included [1,3]. One approach is to use, in addition to satellite-based absolute positioning, terrestrial sources for positioning. Here, the low-frequency navigation systems Loran-C/eLoran and Chayka were developed in the past to provide positioning over wide areas of the earth’s surface. Since several countries have started decommissioning Loran-C sites, it is very unlikely that it will again become a global system in the future. An alternative terrestrial approach is the R-Mode (Ranging Mode) [4]. Here, an existing maritime radio infrastructure will be synchronized with 10 ns accuracy with an external R-Mode reference time [5]. The radio infrastructure is modiﬁed so that it is able to broadcast R-Mode signals or messages,

J. Mar. Sci. Eng. 2020, 8, 209; doi:10.3390/jmse8030209 www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2020, 8, 209 2 of 14 which are carrying the R-Mode time information, together with the communication signal or messages of the legacy service. The user measures either the time of arrival of the R-Mode broadcast or the time difference of the arrival of the broadcast from two R-Mode stations and can from this calculate the distance or distance difference and finally its own position with a trilateration or hyperbolic lateration approach [6–8]. Transmitter sites considered so far are marine radio beacons [6,9] and base stations of the Automatic Identification System (AIS) [6,7,10] or the Very high frequency Data Exchange System (VDES) [11]. These systems share the common factor that they are well distributed along the shore of waters with high traffic density and/or challenging navigation conditions. The R-Mode system is designed as a backup for GNSS. It extends the positioning capabilities of the mariner with additional navigation signals, which are transmitted in different frequency bands and using different propagation paths as compared to GNSS. Furthermore, the R-Mode signals are received with higher signal strength by the user. They are therefore unaffected by the sources of GNSS signal disturbances. Additionally, the R-Mode is a cost efficient way to implement a terrestrial navigation system by reusing existing maritime radio infrastructure. Marine radio beacons are providing a differential GNSS (DGNSS) correction service with Medium Frequency (MF) broadcasts within a coverage of up to 550 km. Using this correction service enables the mariner to perform positioning with an accuracy better than 10 m [12], which is needed for sailing in coastal and restricted waters, harbor entrances, harbor approaches and inland waterways [13,14]. Any adaptation of marine radio beacons on the R-Mode service has to be done without disturbing the legacy service and equipment. One approach that makes use of the entire channel of the 500 Hz–1000 Hz bandwidth, which is dedicated to each radio beacon, is to add two continuous wave signals near the channel boundaries [15,16]. By estimating the phases of the two continuous wave signal components at full seconds, it is possible to measure the distance [15]. AIS is a communication system for exchanging relevant information between ships and base stations operating in the Very High Frequency (VHF) radio band around 162 MHz [17]. It uses a time-division multiple access method to separate the broadcasts of ships and ashore base stations. Each data slot has a length of about 27 ms. Depending on the antenna heights of the transmitter and receiver, the signals can usually be received up to a distance of several 10 km. R-Mode can be implemented on AIS using customized AIS messages, which could use up to five AIS slots [7]. AIS works with a 9.6 kbit/s data rate on two channels with a bandwidth of 25 kHz each. VDES is the successor of AIS. It includes AIS frequencies and services, and has additional channels of up to a 100 kHz bandwidth available for the communication [18]. It also usesthe time-division multiple access method with 2250 slots per minute. With VDES, data rates of 307.2 kbits/s are possible. Using VDES for R-Mode transmissions would significantly increases the R-Mode performance as compared to AIS [11,19]. Therefore, currently the VHF R-Mode activities concentrate on the usage of VDES. This paper focuses on the potential availability of marine radio-beacon signals for R-Mode positioning and support of the integrity evaluation of PNT information. It presumes that all marine radio beacons are upgraded to broadcast MF R-Mode signals that enable ranging [15]. Depending on the number of received R-Mode signals, the mariner’s multi-system ship borne radio navigation receiver (MSR) [20] is able to perform position and timing estimation based on R-Mode or even perform integrity checks of the PNT information. For the position and timing estimation, the signals of four R-Mode stations are necessary [5]. If additional information such as bearing, rough position or timing is available, three R-Mode signals might be sufficient. Any number of R-Mode signals can be used in the MSR for integrity checks of the PNT information. Due to the limited range of marine radio beacons of 50–550 km [21], the R-Mode will not cover the entire world. It is restricted to waters near the shore where higher requirements were defined by the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA) for a backup system [22]. The paper shows which services could be offered based on the areas analyzed to J. Mar. Sci. Eng. 2020, 8, 209 3 of 14 increase the safety of maritime transport with integrity checks, positioning with additional information and full R-Mode-based positioning. The density of maritime traffic in a region depends on many factors, e.g., geographical conditions and nearby important ports. The traffic is therefore far from evenly distributed. With AIS, a system exists that is mandatory for medium and large ships (e.g., merchant and passenger ships). These ships have to implement the International Convention for the Safety of Life at Sea (SOLAS), which means they are obliged to have an AIS transceiver on board [23]. Their transmission of dynamic and static ship data can be used to track single ships. Unfortunately, the range of the AIS transmission is limited to the line of sight. Therefore, only a combination of the received AIS messages from many AIS base stations ashore and AIS satellites enable the generation of a worldwide maritime traffic picture. Within this paper, a combined AIS dataset from shore and satellite AIS receivers is used to estimate the worldwide maritime traffic density and to combine it with the potential availability of the R-Mode service. This paper discusses only the marine radio-beacon component of the R-Mode system. A complete system with VDES R-Mode transmitter sites would increase the availability of the R-Mode further [6,8].

2. Worldwide Potential Service Area for the Medium-Frequency R-Mode Due to the high demand in position and timing backup on a global scope, it is necessary to provide an overview of the possible service area of the R-Mode system using a worldwide coverage prediction. Based on the assumption that marine radio beacons’ nominal ranges provide a reasonable estimate of an R-Mode station range, this coverage prediction provides an overview of possibly covered areas. To compile a comprehensive overview of available marine radio beacons, it was necessary to create a list of all operational radio beacons and their respective position and nominal range. The IALA was commissioned by the International Telecommunication Union (ITU) to coordinate the allocation of the unique identification numbers for the marine radio beacons [24], hence the IALA keeps a list of all worldwide radio beacons [21] and their respective properties. It has to be noted that the IALA gives no guarantee for correct information of the data provided, since the global list is only a compilation of the data provided by national maritime service providers. All subsequent calculations are based on data from the official IALA list dated to March 2019 [21], which is also made available in machine-readable form on an unofficial website [25], which was used for further data processing. A cross-check of the exported list with the IALA list confirms accordance. Worldwide coverage calculations are intended to show a quantifiable evaluation of the potential R-Mode service area in the case of all radio beacons transmitting R-Mode signals. Resulting data is needed to create a worldwide map showing a visually perceptible image of the possible R-Mode service area and calculate the potential coverage of worldwide maritime traffic and high-volume ports. The base parameter for estimating the coverage of a potential service area is the total number of stations in range at a specific point on the map. Since the levels of implementation of the R-Mode system strongly rely on the number of available signals, a coverage map has to give the number of radio beacons in range using a specified spatial resolution. To simplify the process, the grid was generated by equally spaced lateral and longitudinal points using a resolution of 0.05◦ in either direction. Therefore, the resulting data is a uniform grid of equidistant geographical coordinates. Each cell covers, depending on the lateral distance from the equator, an area ranging from 31 to over 20 km2 near 50◦ north/south to near zero at the poles due to the decrease in length of meridians closer to the poles. It has to be noted that the grid is therefore uniform in geographical coordinate distances but not area-wise. The grid values have been calculated by summing up the number of R-Mode stations for which the great circle distance between the grid-cell center and the station is smaller than the nominal range of the station. The values for the great circle distance d were calculated using the Haversine formula given in Equations (1)–(3), where ϕ1 and ϕ2 are the latitude at the first and second coordinate, ∆λ is the J. Mar. Sci. Eng. 2020, 8, 209 4 of 14 difference in longitude between the two coordinates (∆λ = λ λ ) and ∆ϕ represents the difference 2 − 1 between the two lateral coordinates (∆ϕ = ϕ ϕ ). 2 − 1 ! ∆ϕ ∆λ a = sin2 + cos(ϕ ) cos(ϕ ) sin2 (1) 2 1 · 2 · 2 c = 2 asin √a (2) · d = R c (3) · ByJ. Mar. compared Sci. Eng. 20 calculations,20, 8, x FOR PEER it REVIEW could be shown that approximating the earth as a sphere4instead of 16 of an ellipsoid is sufficient for producing desired results. All subsequent calculations are therefore based coordinate, ∆휆 is the difference in longitude between the two coordinates (∆휆 = 휆2 − 휆1) and ∆휑 on therepresents median radius the differenceR of the between earth ofthe 6371 two km,lateral which coordinates is defined (∆휑 = by휑2 the− 휑 WGS-841). reference ellipsoid. When choosing the resolution, it was fundamentally important that the resolution was sufficient ∆휑 ∆휆 (1) 푎 = sin2 ( ) + cos(휑 ) ⋅ cos(휑 ) ⋅ sin2 ( ) to cover all areas in adequate resolution2 by keeping1 the size2 of the matrix2 reasonably small in order to increase the efficient use of the generated coverage-prediction matrix. By comparing different resolution parameters푐 = 2 ⋅ asin provided (√푎) in Figure1, it can be seen that(2) a resolution of 0.10 is insufficient due to finer features of coverage layers (i.e., the number of R-Mode signals ◦ 푑 = 푅 ⋅ 푐 (3) available at this point) becoming lost as a result of the size of grid points available. Increasing the By compared calculations, it could be shown that approximating the earth as a sphere instead resolution to 0.05◦ yields a sufficient result by maintaining a manageable grid size and preserving of an ellipsoid is sufficient for producing desired results. All subsequent calculations are therefore finer grid features. Increasing the resolution to 0.01 would considerably increase the file size due based on the median radius 푅 of the earth of 6371 km◦ , which is defined by the WGS-84 reference to theellipsoid. fact that doubling the resolution results in 4-times the number of elements without having a particularWhen benefit choosing in generating the resolution, a meaningful it was fundamentally statement. Calculationsimportant that havethe resolution been performed was suffi- for all 357 operationalcient to cover radio all areas beacons in adequate contained resolution in the by IALA keeping list [the21] size and of visualized the matrix reasonably in Figure2 small by using in an equidistantorder to cylindrical increase the projection. efficient use of the generated coverage-prediction matrix.

FigureFigure 1. Comparison 1. Comparison of di ofﬀ erentdifferent grid-cell grid-cell resolutions resolutions for for the the number number of available radio radio beacon beacon sig- signals J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 5 of 16 (left tonals right): (left 0.10to right):◦, 0.05 0.1◦0and°, 0.05° 0.01 and◦. 0.01°.

By comparing different resolution parameters provided in Figure 1, it can be seen that a resolution of 0.10° is insufficient due to finer features of coverage layers (i.e., the number of R-Mode signals available at this point) becoming lost as a result of the size of grid points available. Increasing the resolution to 0.05° yields a sufficient result by maintaining a manageable grid size and preserving finer grid features. Increasing the resolution to 0.01° would considerably increase the file size due to the fact that doubling the resolution results in 4-times the number of elements without having a particular benefit in generating a meaningful statement. Calculations have been performed for all 357 operational radio beacons contained in the IALA list [21] and visualized in Figure 2 by using an equidistant cylindrical projection.

FigureFigure 2. Potential 2. Potential R-Mode R-Mode service service area area using using radio radio beacon beacon nominal nominal range.range. The The colors colors from from blue blue to to red indicatered the indicate number the number of available of available beacon beacon signals signals in one in one location. location.

To convert the calculated coverage map into a ratio of area inside and outside of the potential R-Mode service area, each grid cell was correlated with the respected area of the grid cell in km2. From this, it can be deduced that the total area of the earth, which could be covered by one or more R-Mode stations is about 9% of the earth’s surface. This corresponds to an area of 46.8 million km2, of which about 54% is above water and 46% over land (Figure 3).

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Figure 3. Distribution of the potential R-Mode service area.

Figure 4 shows the size of the overall area where exactly one to seven and more potential R- Mode signals could be available. It is clearly visible that only in an area of 4.2 million km2, four and more stations would be available for R-Mode based positioning. It increases by 5.2 million km2 if the chosen positioning approach considers additional information such as bearing of the ranging signals or time from an accurate clock. For the overall area of 46.8 million km2, an integrity check of GNSS-based positioning is possible. This would allow early detection of possible malfunctions or failures in the GNSS receiver or GNSS and would allow the crew of a vessel to intervene quickly and in a timely manner.

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Figure 2. Potential R-Mode service area using radio beacon nominal range. The colors from blue to J. Mar.red Sci. indicate Eng. 2020 the, 8 ,number 209 of available beacon signals in one location. 5 of 14

To convert the calculated coverage map into a ratio of area inside and outside of the potential R-ModeTo convertservice area, the calculated each grid coveragecell was correlated map into awith ratio the of arearespected inside area and of outside the grid of thecell potentialin km2. 2 FromR-Mode this, service it can area,be deduced each grid that cell the was total correlated area of the with earth the respected, which could area ofbe thecovered grid cell by inone km or .more From Rthis,-Mode it can stations be deduced is about that 9% the of totalthe earth area’ ofs surface. the earth, This which corresponds could be coveredto an area by of one 46.8 or moremillion R-Mode km2, 2 ofstations which isabout about 54% 9% is of above the earth’s water surface.and 46% This over corresponds land (Figure to 3). an area of 46.8 million km , of which about 54% is above water and 46% over land (Figure3).

Figure 3. Distribution of the potential R-Mode service area. Figure 3. Distribution of the potential R-Mode service area. Figure4 shows the size of the overall area where exactly one to seven and more potential R-Mode signals could be available. It is clearly visible that only in an area of 4.2 million km2, four and Figure 4 shows the size of the overall area where exactly one to seven and more potential R- more stations would be available for R-Mode based positioning. It increases by 5.2 million km2 if Mode signals could be available. It is clearly visible that only in an area of 4.2 million km2, four and the chosen positioning approach considers additional information such as bearing of the ranging more stations would be available for R-Mode based positioning. It increases by 5.2 million km2 if signals or time from an accurate clock. For the overall area of 46.8 million km2, an integrity check of the chosen positioning approach considers additional information such as bearing of the ranging GNSS-based positioning is possible. This would allow early detection of possible malfunctions or signals or time from an accurate clock. For the overall area of 46.8 million km2, an integrity check of failures in the GNSS receiver or GNSS and would allow the crew of a vessel to intervene quickly and GNSSJ. Mar.-based Sci. Eng. positioning 2020, 8, x FOR is PEER possible. REVIEW This would allow early detection of possible malfunctions 6or of 16 in a timely manner. failures in the GNSS receiver or GNSS and would allow the crew of a vessel to intervene quickly and in a timely manner.

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Figure 4. Single and multiple covered areas with potential Medium Frequency (MF) R-Mode signals. Figure 4. Single and multiple covered areas with potential Medium Frequency (MF) R-Mode sig- Thenals tendency. of the distribution towards single and double covered areas can be explained with the provided service of the marine radio beacons. These support the maritime navigation in coastal areas, portThe approaches,tendency of ports the distribution and inland waterways. towards single Since and no multiple double covered coverage areas is required can be to explained provide GNSSwith correctionsthe provided and service integrity of informationthe marine alongradio thebeacons. coastline, These the support stations arethe distributedmaritime navigation accordingly in tocoastal ensure areas, the most port e ﬃapproaches,cient coverage ports for and service inland providers. waterways. To ensure Since ano continuously multiple coverage available is required service into certain provide areas, GNSS the corrections radio beacon and service integrity areas information have to overlap along at the least coastline, twice. In the some stations areas withare distrib- close coastsuted oraccording internationally to ensure borders, the a most higher efficient density coverage of radio for beacons service can providers be found,. To which ensure results a continu- in a higherously numberavailable of service overlapping in certain service areas, areas. the radio beacon service areas have to overlap at least twice. In someWhen areas examining with close potential coasts R-Mode or international service areas borders, around a thehigher globe, density it can of be radio observed beacons that manycan be potentiallyfound, which interesting results areasin a higher lay within number the rangeof overlapping of radio beacons. service areas. Three examples shown in Figure5 demonstrateWhen theexamining coverage potential of radio beaconsR-Mode in service complex areas marine around environments. the globe, it can be observed that many potentially interesting areas lay within the range of radio beacons. Three examples shown in Figure 5 demonstrate the coverage of radio beacons in complex marine environments.

Figure 5. Potential R-Mode service area: (1) North Europe; (2) Black Sea, Suez, Red Sea and Gulf of Oman and (3) Coast of China and Japan.

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Figure 4. Single and multiple covered areas with potential Medium Frequency (MF) R-Mode signals.

The tendency of the distribution towards single and double covered areas can be explained with the provided service of the marine radio beacons. These support the maritime navigation in coastal areas, port approaches, ports and inland waterways. Since no multiple coverage is required to provide GNSS corrections and integrity information along the coastline, the stations are distributed accordingly to ensure the most efficient coverage for service providers. To ensure a continuously available service in certain areas, the radio beacon service areas have to overlap at least twice. In some areas with close coasts or international borders, a higher density of radio beacons can be found, which results in a higher number of overlapping service areas. When examining potential R-Mode service areas around the globe, it can be observed that

J.many Mar. Sci. potentially Eng. 2020, 8 interesting, 209 areas lay within the range of radio beacons. Three examples shown6 of in 14 Figure 5 demonstrate the coverage of radio beacons in complex marine environments.

FigureFigure 5.5. PotentialPotential R-ModeR-Mode service area: (1) North Europe; (2) BlackBlack Sea,Sea, Suez,Suez, RedRed SeaSea andand GulfGulf ofof OmanOman andand ((33)) CoastCoast ofof ChinaChina andand Japan.Japan.

J. Mar.The Sci. Eng. areas 2020 around, 8, x; doi: the FOR North PEER REVIEW of Europe in Figure5(1) consist of severalwww.mdpi.com/journal/ challenging regions,jmse including the English Channel, the traﬃc separation scheme of Terschelling and the Skagerrak passage. Here, an increased demand for high reliability of PNT data exists. These areas show coverage well within the bounds of positioning using R-Mode signals. Areas around the Mediterranean, especially the approaches and passage through the Suez Canal in Figure5(2), are covered by marine radio beacons, although the coverage at the moment is still more in the 1–2-fold range. Support with PNT integrity information would therefore be feasible. The last example is the area around the south-eastern coast of China as well as Japan and Korea in Figure5(3), which shows a particularly dense coverage and provides a good basis for the use of the R-Mode as a backup system. In particular, the well-covered and heavily frequented ports along the Chinese coast oﬀer a good basis for the use of the R-Mode.

3. Worldwide Maritime Traffic Density To introduce a benchmark for the assessment of the potential R-Mode area coverage, AIS traffic densities were calculated utilizing a global AIS dataset. AIS data form a good basis for the compilation of maritime situational images due to the legal obligation of ships to be equipped with AIS transceivers in accordance with SOLAS Chapter V [23]. Several processing steps were necessary for the creation of maritime situational images and the use of the received data. These are briefly described and explained below. The traffic density k, which was used in the paper, is defined as the average number of ships N per area (unit km2). It is calculated for the grid cell with size A as shown in Equation (4).

N k = (4) A In order to simplify the simultaneous analysis of coverage prediction and traffic density, the same grid resolution of 0.05◦ was used throughout. JAKOTA Cruise System GmbH provided a global AIS dataset containing dynamic and static data of worldwide ship traffic. Presented data in this paper shows an excerpt of the data consisting of 170 J. Mar. Sci. Eng. 2020, 8, 209 7 of 14 million dynamic AIS records representing about 90,000 different Maritime Mobile Service Identities (MMSI). The analyzed data has been restricted to Class A AIS messages only, due to merchant ships being the primary user of such a backup system to improve safety during critical phases of navigation (e.g., port approaches, narrow traffic separation schemes, shallow waters, etc.). AIS data providers typically use one or more networks of AIS base stations and several AIS satellites as sources for their worldwide AIS datasets. Even with this high effort, gaps in the track of single ships cannot, however, be avoided. This results in gaps from several minutes up to hours when observing a single ship. To overcome the problem of smaller gaps and to reduce the number of data for the evaluation of the traffic density, it was decided to split the day into 96 equal periods of 15 min length and take the position from the first dynamic AIS message in this period as the location of the ship in this period. The value of 15 min was chosen empirically. It should be large enough to have continuous tracks of the ship (at least one AIS message per period) but not so large that it jumps from one to the next period significantly in relation to the size of the radio beacon service area. A fast vessel with a speed of 20 kn will sail about 9 km in 15 min. That is only a small fraction of the nominal range of most radio beacons, which, for the 357 radio beacons, is on average 250 km. Larger gaps in the tracks of a ship that are at least 15 min long were filled with interpolated positions considering the ship positions before and after the gap. In order to prevent the erroneous interpolation in the case of insufficient data in the records, only ships with more than three observations were considered for the intermediate gap-patching. This applied to around 90% of all data being 2 J.eligible Mar. Sci. for Eng. interpolation. 2020, 8, x FOR PEER Figure REVIEW6 shows color-coded the tra ffic density as ship per km for the8 cases of 16 without and with interpolation. Here, the average number N of ships per grid cell, which goes into goesEquation into (4),Equation was calculated (4), was bycalculated summing by up summi for allng ships up for the all number ships ofthe periods number that of the periods ship stayed that the in shipthis gridstayed cell in and this dividing grid cell it and by thedividing number it by of the periods number (96). of periods (96).

FigureFigure 6. 6. TrafficTraﬃc density derived from non non-interpolated-interpolated (a) and interpolated (b)) AISAIS dataset.dataset.

Figure6 6clearly clearly shows shows the success the success of the of interpolation the interpolation approach. approach. In the case In of the non-interpolated case of non- interpolateddata (Figure6 a),data many (Figure ship 6 tracksa), many in the ship China tracks Sea in and the also China along Sea the and Chinese also along coastline the showChinese recurring coast- linegaps. show With recurring interpolation gaps. (Figure With interpolation6b), the tracks (Figure appear 6 inb), the the data tracks presentation appear in mostlythe data as presentation continuous mostlylines. Only as continuous the track from lines. 10,000 Only ships the track out of from the around 10,000 90,000ships out MMSI of the could around not be 90,000 interpolated MMSI duecould to notlimited be interpolated AIS data for due the ship.to limited Figure AIS6 also data shows for the that ship the. interpolation Figure 6 also generates shows that mostly the interpolation realistic ship generates mostly realistic ship tracks. The ships sail over the water. Only in some regions with narrow waterways were a few ships seen to be sailing over land for a short time. Figure 7 shows the world’s averaged maritime traffic density on one day in the middle of 2016. Clearly visible here are the main traffic routes, which connect the world’s busiest ports and the increased traffic density near these ports as well as in straits. Furthermore, Figure 7 shows a concentration of the maritime traffic particularly along the coastlines of America, Europe, Asia and Africa. This fits very well to the distribution of marine radio beacons in America, Europe and Asia (Figure 2).

J. Mar. Sci. Eng. 2020, 8, x; doi: FOR PEER REVIEW www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 8 of 16 goes into Equation (4), was calculated by summing up for all ships the number of periods that the ship stayed in this grid cell and dividing it by the number of periods (96).

Figure 6. Traffic density derived from non-interpolated (a) and interpolated (b) AIS dataset.

Figure 6 clearly shows the success of the interpolation approach. In the case of non- interpolated data (Figure 6a), many ship tracks in the China Sea and also along the Chinese coastline show recurring gaps. With interpolation (Figure 6b), the tracks appear in the data presentation mostlyJ. Mar. Sci. as Eng. continuous2020, 8, 209 lines. Only the track from 10,000 ships out of the around 90,000 MMSI could8 of 14 not be interpolated due to limited AIS data for the ship. Figure 6 also shows that the interpolation generates mostly realistic ship tracks. The ships sail over the water. Only in some regions with nar- rowtracks. waterways The ships were sail overa few the ships water. seen Only to be in sailing some over regions land with for narrowa short time. waterways were a few ships seenFigure to be sailing 7 show overs the land world’s for a averaged short time. maritime traffic density on one day in the middle of 2016. ClearlyFigure visible7 shows here theare world’sthe main averaged traffic routes maritime, which tra connectffic density the onworld’s one day busiest in the ports middle and ofthe 2016. in- creasedClearly visibletraffic heredensity are thenear main these tra portsffic routes, as well which as in connect straits. the Furthermor world’s busieste, Figure ports 7 andshows the a increased concen- trationtraffic density of the maritime near these traffic ports particularly as well as in along straits. the Furthermore, coastlines of Figure America,7 shows Europe, a concentration Asia and Africa. of the Thismaritime fits very traffi wellc particularly to the distribution along the of coastlines marine radio of America, beacons Europe, in America, Asia andEurope Africa. and ThisAsia fits(Figure very 2well). to the distribution of marine radio beacons in America, Europe and Asia (Figure2).

J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 9 of 16

Figure 7. Average maritime traffic density based on an interpolated AIS dataset for one day. Figure 7. Average maritime traffic density based on an interpolated AIS dataset for one day. The underlying dataset can be broken down according to the distribution shown in Figure 8. In J. Mar. Sci. Eng. 2020, 8, x; doi: FOR PEER REVIEW www.mdpi.com/journal/jmse orderThe to achieve underlying the division dataset canof the be database broken downinto ship according types, the to theMMSI distribution of each dynamic shown dataset in Figure was8. Incorrelated order to achievewith the the corresponding division of the MMSI database in a intostatic ship database types, containing the MMSI of all each MMSIs dynamic of the dataset respective was correlatedyear. The database with the correspondingof the static data MMSI records in a was static generated database from containing an extended all MMSIs database of the of respective the data year.provider. The databaseThe types of of the ships static considered data records in this was paper generated only refer from to an the extended already database mentioned of theClass data A provider.AIS. Looking The typesat the of individual ships considered ship types, in this it papercan be only seen refer that totankers, the already cargo mentioned ships and Class passengers A AIS. Lookingaccount atfor the about individual 50% of shipthe ships types, observed it can be seenand thatthus tankers,make up cargo a significant ships and proportion. passengers Further- account formore, about it can 50% be of seen the shipsthat 21% observed of the andships thus could make not up be a assigned significant to proportion.any ship type Furthermore, at all, as static it can data be seenfor the thatse 21%MMSI of thewere ships not couldavailable. not beOf assignedthe static to data any 5% ship contained type at all, ship as statictypes datathat forare thesenot defined MMSI werein the not official available. AIS specificationOf the static data or that 5% are contained stated shipas “Not types available” that are not according defined to in the oofficialfficial AIS AIS specificationspecification. or that are stated as “Not available” according to the official AIS specification.

Figure 8. Breakdown of AIS dataset by ship type. Figure 8. Breakdown of AIS dataset by ship type. 4. Potential Availability of the R-Mode Service for Maritime Traffic 4. Potential availability of the R-Mode service for maritime traffic To understand the potential support for maritime traffic that the R-Mode service could provide, a quantitativelyTo understand comparison the potential between support the radio-beacon for maritime coverage traffic that of Figurethe R-Mode2 and the service tra ffi couldc density provide, a quantitatively comparison between the radio-beacon coverage of Figure 2 and the traffic density shown in Figure 7 was carried out. For each area of single to eight-fold and more coverage, the number of ships over the day in these areas was calculated. This number was divided by the total number of vessels counted to determine the percentage of ships within the desired coverage level. These calculations were performed for the areas with one to eight and more R-Mode signals available. Figure 9 shows the calculation result for the analyzed day. The percentage of the world’s ship traffic in red overlays the total area single to eight-fold and more covered area of potential R-Mode stations in blue. If the traffic was homogenously distributed over the world’s sea area, it would be expected that the percentage of the ships would follow the size of the covered area. Instead, a max- imum of ship traffic at three-fold coverage can be observed. Even the four-fold and five-fold covered areas are heavily frequented by ships. In sum, around 67% of worldwide maritime traffic operates inside the potential R-Mode service area. The R-Mode would support these ships with integrity information. For 40% of the world’s ships, the R-Mode could provide a position if additional information exists, and for 25% of the ships, positioning with the R-Mode is possible.

J. Mar. Sci. Eng. 2020, 8, x; doi: FOR PEER REVIEW www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2020, 8, 209 9 of 14 shown in Figure7 was carried out. For each area of single to eight-fold and more coverage, the number of ships over the day in these areas was calculated. This number was divided by the total number of vessels counted to determine the percentage of ships within the desired coverage level. These calculations were performed for the areas with one to eight and more R-Mode signals available. Figure9 shows the calculation result for the analyzed day. The percentage of the world’s ship traffic in red overlays the total area single to eight-fold and more covered area of potential R-Mode stations in blue. If the traffic was homogenously distributed over the world’s sea area, it would be expected that the percentage of the ships would follow the size of the covered area. Instead, a maximumJ. Mar. Sci. Eng. of 20 ship20, 8, trax FORffic PEER at three-fold REVIEW coverage can be observed. Even the four-fold and five-fold10 of 16 covered areas are heavily frequented by ships.

Figure 9. Comparison of R R-Mode-Mode coverage and traffic traﬃc density.density.

InThe sum, numbers around in 67%Figure of worldwide9 can be explained maritime by tra goodffic operates coverage inside of the the R- potentialMode in traffic R-Mode-intensive service area.areas. TheThe R-Moderesult of wouldfurther supportinvestigations these shipsinto reasons with integrity for the high information. amount of For traffic 40% in of the the potential world’s ships,R-Mode the service R-Mode area could is presented provide ain position Table 1. if additional information exists, and for 25% of the ships, positioning with the R-Mode is possible. The numbersTable 1. inTop Figure nine c9ontainer can be explainedports and their by goodrespective coverage potential of theR-Mode R-Mode coverage in tra [16]ffi. c-intensive areas. The result of further investigations into reasons for the high amount of traffic in the potential Top 9 ports worldwide (by container handling) R-Mode service area is presented in TableNingbo-1. Guangzhou Hong Kong, Shanghai Singapore Shenzhen Zhousan Harbor Busan S.A.R Quingdao Tianjin Number of Table 1. Top nine container ports and their respective potential R-Mode coverage [16]. R-Mode 3 4 2 5 1 3 3 3 3 Top 9 Ports Worldwide (by Container Handling) stations Shanghai Singapore Shenzhen Ningbo-Zhousan Guangzhou Harbor Busan Hongkong, S.A.R Quingdao Tianjin Number of 3 4 2 5 1 3 3 3 3 R-ModeThe stations table shows the top nine container ports worldwide according to a current ranking provided by the World Shipping Council [26] and their respective coverage by marine radio beacons. The presentedThe table shows analysis the supports top nine containerthe assumption ports worldwide that particularly according traffic to a-intensive current ranking areas have provided a good by theextension World Shippingwith maritime Council antennas [26] and and their are respective therefore coverage suitable byfor marine the implementation radio beacons. of The the presented R-Mode analysissystem. A supports visual representation the assumption of that the particularlyvalues listed tra inffi Tablec-intensive 1 in combination areas have awith good the extension traffic densi- with maritimeties determined antennas shows and arehigh therefore accumulation suitable of for maritime the implementation traffic at intersections of the R-Mode with system. good coverage. A visual representationSuch visual comparison of the values is provided listed in Table below1 in in combination Figure 10, showing with the the tra fficoveragec densities and determined traffic density shows at highthe port accumulation locations. of maritime traffic at intersections with good coverage. Such visual comparison is provided below in Figure 10, showing the coverage and traffic density at the port locations.

J. Mar. Sci. Eng. 2020, 8, x; doi: FOR PEER REVIEW www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 11 of 16

J.J. Mar. Mar. Sci.Sci. Eng.Eng. 20202020,,8 8,, 209x FOR PEER REVIEW 1011of of 1416

Figure 10. Comparison of location of the top nine container ports in respect to R-Mode coverage (a) andFigure traffic 10. densityComparison (b). of location of the top nine container ports in respect to R-Mode coverage (a) andFigure traffi 10.c densityComparison (b). of location of the top nine container ports in respect to R-Mode coverage (a) Forand atraffic more density in-depth (b). analysis of the shares in ships in the potential R-Mode service area, the NorthFor Sea a moreand Baltic in-depth Sea analysis regions ofwere the sharesanalyzed. in ships The inNorth the potential Sea, as shown R-Mode in service Figure area, 11, shows the North an overallSea andFor good Baltica more coverage Sea in regions-depth along analysis were the analyzed.coasts, of the with shares The a peak North in ships in Sea, coverage in as the shown potentialaround in Figure the R- ModeEnglish 11, shows service Channel. an area, overall Due the togoodNorth the coveragegeometric Sea and alongBaltic distribution theSea coasts,regions of the with were R-Mode a peakanalyzed. stations in coverage The on North both around sidesSea, theasof shownthe English Channel, in Channel. Figure three 11 Duestations, shows to the oran moregeometricoverall can good be distribution received coverage simultaneously. of along the R-Mode the coasts, stations Especially with on a peak both the approaches sidesin coverage of the Channel,for around Rotterdam the three English and stations Hamburg Channel. or more have Due can abeto continuous receivedthe geometric simultaneously. coverage distribution of multiple Especially of the stations.R the-Mode approaches Thestations passage foron Rotterdamboth between sides Denmarkandof the Hamburg Channel, and have Sweden three a continuous stations (Skager- or rak/Kattegat)coveragemore can of be multiple receivedshows stations.a consistentlysimultaneously. The passage good Especially coverage between theof Denmark up approaches to eight and and Sweden for nineRotterdam (Skagerrak stations and in/Kattegat) highHamburg-risk shows areas have nearaa consistently continuous narrow channels good coverage coverage and of highmultiple of- updensity to stations. eight sections and The nine of passagethe stations passage. between in high-riskPlease Denmark note areas an near andarea Swedennarrowin the middle channels (Skager- of theandrak/Kattegat) North high-density Sea ,shows which sections ahas consistently no of thecoverage. passage. good Due coverage Please to the note distributionof up an to area eight in ofthe and large middle nine oil stationsfields of the and Northin highwind Sea,-risk farms, which areas a possiblehasnear no narrow coverage. retrofitting channels Due of andR to-Mode the high distribution-capable-density transmission sections of large of oil the infrastructure fields passage. and Please wind has farms, noteto be an considered a area possible in the retrofittingin middle order toof ensureofthe R-Mode-capable North continuous Sea, which coverage transmission has no of coverage. the infrastructure North Due Sea. to Alternatively, the has distribution to be considered the of R -largeMode in orderoil could fields to be ensureand implemented wind continuous farms, on a thecoveragepossible basis retof rofittingthe NorthAIS orof Sea. VDESR-Mode Alternatively, of- capablethe oil platforms, transmission the R-Mode which infrastructure could could be implementedenable has po tositioning. be onconsidered the This basis problem in of order the AIS isto notorensure VDES considered continuous of the oilto be platforms, coverage particularly of which the drastic North could due Sea. enable to Alternatively, the positioning. absolutely the This low R- Modeproblemlevel ofcould shipping is not be consideredimplemented traffic in to this beon particularlyarea,the basis as can of be drasticthe seen AIS by due or comparing VDES to the of absolutely the the oil analysis platforms, low levelof the which of traffic shipping could density.tra enableffi c in po thissitioning. area, as This can beproblem seen by is comparingnot considered the analysis to be particularly of the traffi cdrastic density. due to the absolutely low level of shipping traffic in this area, as can be seen by comparing the analysis of the traffic density.

Figure 11. Comparison between the potential R-Mode coverage in the North Sea (a) and the traﬃc Figure 11. Comparison between the potential R-Mode coverage in the North Sea (a) and the traffic density in the same area (b). density in the same area (b). Figure 11. Comparison between the potential R-Mode coverage in the North Sea (a) and the traffic Further consideration of the adjacent Baltic Sea region reveals comparable coverage (Figure 12). density in the same area (b). For the use of the Baltic Sea as a test bed for the implementation of the R-Mode system [8], good coverage J. Mar. Sci. Eng. 2020, 8, x; doi: FOR PEER REVIEW www.mdpi.com/journal/jmse

J. Mar. Sci. Eng. 2020, 8, x; doi: FOR PEER REVIEW www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 12 of 16 J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 12 of 16 Further consideration of the adjacent Baltic Sea region reveals comparable coverage (Figure J.12 Mar.). ForFurther Sci. the Eng. use 2020 consideration of, 8 ,the 209 Baltic ofSea the as a adjacent test bed Baltic for the Sea implementation region reveals of comparable the R-Mode coveragesystem [8] (Figure,11 good of 14 coverage12). For the is usea basic of the requirement. Baltic Sea as With a test comparative bed for the implementationconsideration of ofthe the traffic R-Mode density system in the [8] ,Baltic good Seacoverage region, is aas basic shown requirement. in Figure 12With on comparativethe right side, consideration an increase of thehigh traffic correspondence density in the between Baltic is a basic requirement. With comparative consideration of the traﬃc density in the Baltic Sea region, as trafficSea region,-intensive as shown areas andin Figure the potential 12 on the R-Mode right serviceside, an area increase can be of found. high correspondence Due to the high betweenpropor- shown in Figure 12 on the right side, an increase of high correspondence between traﬃc-intensive tiontraffic of- intensivepotential areasR-Mode and service the potential areas with R-Mode four serviceand more area available can be found. signals Due per to grid the cell, high posi propor-tion- areas and the potential R-Mode service area can be found. Due to the high proportion of potential ingtion in of these potential areas R could-Mode probably service areasbe achieved with four when and implementing more available the signals R-Mode. per grid cell, position- R-Modeing in these service areas areas could with probably four and be achieved more available when implementing signals per grid the cell, R-Mode. positioning in these areas could probably be achieved when implementing the R-Mode.

Figure 12. Comparison between the potential R-Mode coverage in the Baltic Sea (a) and the traffic Figure 12. Comparison between the potential R-Mode coverage in the Baltic Sea (a) and the traffic densityFigure 12.in theComparison same area between(b). the potential R-Mode coverage in the Baltic Sea (a) and the traffic density in the same area (b). density in the same area (b). A breakdown ofof thethe shipship typestypes into into passenger passenger ships, ships, tankers tankers and and cargo cargo ships ships reveals reveals some some minor mi- dinorfferences differencesA breakdown in the in the potentialof thepotential ship R-Mode types R-Mode into support support. passenger Figure Passenger ships, 13. Passengertankers ships showand ships cargo a clear show ships increase a reveals clear in increase somepotential mi- in potentialcoveragenor differences coveragein the inrange inthe the potentialof rangefour–six of R four–six-fold--foldMode coverage. support. coverage. In Passenger absolute In absolute shipsterms, show 86% terms, ofa clear 86%all passenger ofincrease all passenger inships potential oper- ships operateatecoverage within within in the the R therange-Mode R-Mode of area. four area. –Thissix-fold This significant coverage. significant share In shareabsolute of passenger of passenger terms, ships 86% ships allowof all allowed edpassenger a large a large shipspart partof oper- the of thepassengerate passenger within shipsthe ships R -theMode thepossible possiblearea. Thispositioning positioning significant with with share R- R-ModeMode of passenger (four (four-fold)-fold) ships with with allow increasing increasinged a large accuracy accuracy part of of the positioningpassenger ships solutionsolution the andandpossible possible possible positioning integrity integrity checkwith check R (four -(Modefour plus-fold plus (four-fold-fold) coverage). covera withge). increasing This This distribution distribution accuracy was wasof to the beto expectedbepositioning expected due solutiondue to the to high theand high proximity possible proximity integrity of passenger of passengercheck ships (four to ships plus the coast -tofold the andcovera coast thege). highand This frequencythe distribution high frequency of calls was from ofto ports.callsbe expected from When ports. due looking When to the at looking cargohigh proximity ships at cargo and shipsof tankers, passenger and only tankers, shipsminor only to di theff minorerences coast differences canand bethe seen highcan in be frequency the seen diff inerent the of levelsdifferentcalls from of coverage.levels ports. of When coverage. This looking distribution This at distribution cargo is notships surprising isand not tankers, surprising as these only as ships minor these account differences ships account for the can largest forbe seenthe portionlargest in the ofportiondifferent ships. of levels ships. of coverage. This distribution is not surprising as these ships account for the largest portion of ships.

Figure 13. Comparison of R-Mode coverage and traffic density. Figure 13. Comparison of R-Mode coverage and traffic density. 5. Limits of the StudyFigure 13. Comparison of R-Mode coverage and traffic density. J. Mar.The Sci. Eng. current 2020, 8 study, x; doi:set FOR the PEER focus REVIEW on the potential availability of MF R-Modewww.mdpi.com/journal/ signals underjmse the assumptionJ. Mar. Sci. Eng. that 2020 all, 8, x; marine doi: FOR radio PEER beacons REVIEWwould, in addition to the legacy signal,www.mdpi.com/journal/ also transmit R-Modejmse J. Mar. Sci. Eng. 2020, 8, 209 12 of 14 signal components and that the R-Mode service area is equal to the service area of the legacy service. The results of tests in the North Sea [27] show the feasibility of the technical approach. Unfortunately, the given size of the radio-beacon service area in the IALA list is only an indicator for the size of the R-Mode service area. Measurements show that the R-Mode signal of Heligoland (Germany) could be received in the United Kingdom at distances of about 500 km during the daytime, even though the given nominal range of Heligoland is 285 km [9,21]. During the night, the R-Mode service area decreases [27]. The observed R-Mode signal availability can be explained with the process of measuring the distance by estimating the phase of the R-Mode signal components [27], which propagates as a ground-wave. The achievable accuracy strongly depends on the signal-to-noise or signal-to-interference ratio. As with free-space radio waves, the R-Mode signal strength decreased with distance. Additional attenuation is caused on the propagation path by decreased ground conductivity [28,29]. The radio beacon service area is therefore typically very irregular (shown in Figure 18 of [16]), which is typically approximated as a circle with the given nominal range as radius [30]. The noise also has some dependencies on the time of the day and the year as well as the region [31]. During the night the sky-wave, which is reflected at the E-layer of the ionosphere, is subjected to weaker damping than during the day. Therefore, both sky-wave and ground-wave interfere at the user side and disturb phase measurements in the night [27]. This effect is not considered in the nominal range but has to be considered for the R-Mode, because it will have an impact on the ranging and positioning accuracy [16]. Future studies should consider these effects as well as the geometry of the radio beacons. Using AIS for the generation of the traffic maps has a few shortcomings, which the authors have summarized as follows. Each ship has to send its own correct position report with an update rate of seconds to minutes. Many receivers with worldwide distribution are needed to forward the information to a central data-processing and storage facility. For several reasons, this information-provision and forwarding chain is interrupted from time to time, as seen in the data from JAKOTA Cruise System GmbH. The same limitations were also determined for the data of other AIS data providers. This study was based on the tracks of worldwide-operating SOLAS ships. In order to mitigate a weighting of AIS traffic data due to uneven distribution of received datasets, missing ship positions have been interpolated with a straight line and constant velocity. This type of interpolation was considered sufficient because ships usually follow a predictable path, which is only in rare cases accompanied by incomprehensible course changes. However, it cannot be completely excluded that the interpolated tracks are crossing land masses. The evaluated sample of about 90,000 ships was very large and distributed worldwide. Due to limited availability of AIS data and processing capacity, this study was limited to the 4th July 2016. In order to generate a further in-depth analysis of possible user groups of the R-Mode system from AIS data, a broader analysis is necessary and could be realized by evaluating more extensive datasets (1 year or more).

6. Conclusions The maritime community is looking for a backup system to GNSS that can support navigators and new maritime applications for operation in challenging environments. Especially in areas with high traffic density, limited fairways or shallow waters, as it is often the case in coastal areas, ports and port approaches, there is the need for resilient provision of PNT data. The R-Mode, a terrestrial positioning system that utilizes shore maritime radio infrastructure, could fill this gap. Under the assumption that the currently declared marine radio-beacon service areas would be the same for R-Mode, the authors deduced that especially the coastlines of the northern hemisphere would be well covered by R-Mode signals. In the southern hemisphere, only areas with high traffic density or the coastlines of economically strong countries would benefit from R-Mode on radio beacons. Due to J. Mar. Sci. Eng. 2020, 8, 209 13 of 14 the limited nominal range of 250 km on average and their limited number (357), the radio beacons cover only about 7% of the earth’s water surface. For a backup system, the overlap of the R-Mode station service areas is important. In 4.2 million km2, R-Mode-based positioning with four and more available signals is possible. Outside this R-Mode core region, the user can benefit from R-Mode with positioning with additional information or integrity check for any other PNT data. The R-Mode system shall support maritime operations. Therefore, the authors compared the covered area with the averaged maritime traffic, which was deduced from a 1-day global AIS dataset. The results show that a significant proportion of ship traffic of 67% operated over the day in the area of at least one potential R-Mode station. For 25% of the ships, positioning with R-Mode was possible. This underlines that the marine radio beacons support the majority of maritime traffic. For certain areas with high traffic density and the most important container ports, three and more beacon signals were often available. Passenger ships would benefit over-proportionally from the R-Mode service. The study was based on the given nominal ranges of the marine radio beacons. This is a good approximation of the R-Mode service area. In reality, the R-Mode performance degraded over distance and depended on the time of the day and on the direction of radiation. Future studies that evaluate the number of ships that would operate in an area with certain R-Mode positioning accuracy therefore have to take this into consideration. Measurements of the R-Mode signal strength and noise are helpful in calibrating the channel model. Beside marine radio beacons, AIS or VDES base stations could also be the source of R-Mode ranging signals [6]. These stations typically support the same coastline but with reduced range. It could be shown for the North Sea and Baltic Sea that the combination of all R-Mode signal sources makes positioning in wide areas of these regions possible. Yet to be proven is how R-Mode on AIS/VDES would increase the worldwide R-Mode service quality.

Author Contributions: Conceptualization, S.G.; Data curation, P.K.; Formal analysis, P.K. and S.G.; Investigation, P.K.; Project administration, S.G.; Software, P.K.; Supervision, S.G.; Visualization, P.K.; Writing–original draft, P.K. and S.G.; Writing–review & editing, P.K. and S.G. All authors have read and agreed to the published version of the manuscript. Funding: This study has been conducted in the framework of the institutionally funded project ‘Automated Aids for Safe and efficient vessel traffic processes (A++Set)’ of the German Aerospace Center (DLR). Acknowledgments: The authors thank JAKOTA Cruise System GmbH for providing the AIS dataset for the analysis of global maritime traffic. Conflicts of Interest: The authors declare no conflict of interest.

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