Space-based detection of AIS signals: Results of a feasibility study into an operational space-based AIS system

Hennepe, F. te; Rinaldo, Rita; Ginesi, Alberto; Tobehn, C.; Wieser, Matthias; Olsen, Øystein; Helleren, Øystein; Challamel, R.; Storesund, Frode

doi:10.1109/asms-spsc.2010.5586862

Cited by 12 publications

(7 citation statements)

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“…This indicates that the existence of AIS default values of a single on-board sensor chosen for analysis cannot be perceived only in terms of two categories of vessels: those that do not transmit AIS default values at all, and those that broadcast only AIS default values. Results obtained from other researchers, like [6] or [12], to mention a few, confi rm this assumption.…”

Section: Occurrence Of Ais Default Data Under Real Conditions / Pojavmentioning

confidence: 52%

“…For the purpose of generating the AIS broadcast timelines, the set of all possible Class A AIS transmission intervals specifi ed by [8, p.8] was defi ned in seconds by: (6) In order to create the set of the external sensor data rates, the following data set was used: 7Set B covers sensor data rates ranging from a high performance feed of 20 measurements per second down to a near failure data provision of 1 measurement per 200 seconds.…”

Section: Relationship Between the Sensor Data Rate And The Occurrencementioning

confidence: 99%

“…The set of the relative time shifts of the timeline starting points in seconds was provided by: (8) where a is the AIS broadcast interval selected by the loop iterating over the set defi ned in Equation (6).…”

Section: Relationship Between the Sensor Data Rate And The Occurrencementioning

confidence: 99%

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Occurrence of Unknown Sensor Data within AIS Dynamic Messages

Banyś¹,

Heymann²,

Gucma³

2020

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For more than a decade, the Automatic Identifi cation System (AIS) has contributed to increasing the safety of navigation at sea. Despite the benefi ts of the system, AIS messages shared between vessels and the AIS dynamic data transferred to the Portable Pilot Units may contain unknown values of sensor data if the sensor data on board becomes either unavailable or undeliverable for any reason. In this paper, an experiment is conducted to analyse the performance of an AIS transponder during a virtual sea voyage. By altering the sensor data rate it is possible to cause the AIS transponder to output AIS messages with unknown sensor data. After performing the experiment, a generic approach is used in order to establish a correlation between the sensor data rate and the relative occurrence frequency of AIS unknown values. This leads to the formulation of a simple equation which describes the interdependence between the interval of sensor data provision, the age of the sensor data allowed by the AIS transponder and the percentage of unknown data within the AIS data output. Sažetak Više od desetljeća sustav automatske identifi kacije (AIS) pridonosi povećanju sigurnosti plovidbe na moru. Unatoč prednostima sustava, AIS poruke dijeljene između plovila, kao i AIS dinamički podaci preneseni na prijenosne peljarske jedinice, mogu sadržavati nepoznate vrijednosti podataka senzora ako ti podaci na ploči iz bilo kojeg razloga postanu nedostupni ili neisporučivi. U radu je proveden eksperiment za analizu performansi AIS transpondera tijekom virtualnog putovanja na moru. Promjenom brzine podataka senzora moguće je podesiti izlaz AIS poruka s nepoznatim podacima senzora s AIS transpondera. Nakon izvođenja eksperimenta koristio se generički pristup kako bi se uspostavila povezanost između brzine podataka senzora i relativne učestalosti pojavljivanja nepoznatih vrijednosti AIS-a. Time se dolazi do jednostavne jednadžbe koja opisuje međuovisnost intervala pružanja senzorskih podataka, starosti senzorskih podataka koje dopušta AIS transponder i postotka nepoznatih podataka u izlazu AIS podataka.

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Section: Occurrence Of Ais Default Data Under Real Conditions / Pojavmentioning

confidence: 52%

Section: Relationship Between the Sensor Data Rate And The Occurrencementioning

confidence: 99%

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Occurrence of Unknown Sensor Data within AIS Dynamic Messages

Banyś¹,

Heymann²,

Gucma³

2020

Naše more

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“…The outputs of such activities are used by various agencies for the sustainable management of the ocean and its resources. One of the most popular maritime surveillance services is the automatic identification system (AIS) for the precise positioning of moving ships [1]. However, most of the vessels and small boats are not equipped with the AIS transceivers.…”

Section: Introductionmentioning

confidence: 99%

Range-Doppler Based CFAR Ship Detection with Automatic Training Data Selection

et al. 2019

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Ship detection is an essential maritime security requirement. Current state-of-the-art synthetic aperture radar (SAR) based ship detection methods employ fully focused images. The time-consuming processing efforts required to generate these images make them generally unsuitable for real time applications. This paper proposes a novel real time oriented ship detection strategy applicable to range-compressed (RC) radar data acquired by an airborne radar sensor during linear, circular and arbitrary flight tracks. A constant false alarm rate (CFAR) detection threshold is computed in the range-Doppler domain using suitable distribution functions. Detection in range-Doppler has the advantage that principally even small ships with a low radar cross section (RCS) can be detected if they are moving fast enough so that the ship signals are shifted to the exo-clutter region. In order to determine a robust threshold, the ocean statistics have to be described accurately. Bright target peaks in the background ocean data bias the statistics and lead to an erroneous threshold. Therefore, an automatic ocean training data extraction procedure is proposed in the paper. It includes (1) a novel target pre-detection module that removes the bright peaks from the data already in time domain, (2) clutter normalization in the Doppler domain using the remaining samples, (3) ocean statistics estimation and (4) threshold computation. Various sea clutter models are investigated and analyzed in the paper for finding the most suitable models for the RC data. The robustness and applicability of the proposed method is validated using real linearly and circularly acquired radar data from DLR’s (Deutsches Zentrum für Luft- und Raumfahrt) airborne F-SAR system.

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“…The systems operating include the VesselSat series developed by the ORBCOMM company (Luxspace, 2013; ORBCOMM, 2013a), AprizeSat series by SpaceQuest company (SpaceQuest, 2013; DNEPR, 2013) in America, Rubin series by OHB-System company (Holsten et al, 2009a, 2009b; Hennepe et al, 2010) in Germany, Nanosatellite Tracking of Ships (NTS) by COM DEV (Posada et al, 2011) in Canada and AISSat series by the Norwegian Defence Research Establishment (FFI) (Hannevik et al, 2010). To improve the surveillance services, space-borne AIS constellation plans have been deployed.…”

Section: Introductionmentioning

confidence: 99%

Ship Surveillance by Integration of Space-borne SAR and AIS – Review of Current Research

Zhao

Xing

et al. 2013

J. Navigation

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Ship surveillance is important for maritime security and safety. It plays important roles in many applications including ocean environment monitoring, search and rescue, anti-piracy and military reconnaissance. Among various sensors used for maritime surveillance, space-borne Synthetic Aperture Radar (SAR) is valued for its high resolution over wide swaths and all-weather working capabilities. However, the state-of-the-art algorithms for ship detection and identification do not always achieve a satisfactory performance. With the rapid development of space-borne Automatic Identification System (AIS), near real-time and global surveillance has become feasible. However, not all ships are equipped with or operate AIS. Space-borne SAR and AIS are considered to be complementary, and ship surveillance using an integrated combination has attracted much attention. In order to summarize the achievements and present references for further research, this paper attempts to explicitly review the developments in previous research as the basis of a brief introduction to space-borne SAR and AIS.

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Space-based detection of AIS signals: Results of a feasibility study into an operational space-based AIS system

Cited by 12 publications

References 0 publications

Occurrence of Unknown Sensor Data within AIS Dynamic Messages

Occurrence of Unknown Sensor Data within AIS Dynamic Messages

Range-Doppler Based CFAR Ship Detection with Automatic Training Data Selection

Ship Surveillance by Integration of Space-borne SAR and AIS – Review of Current Research

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