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- W3157871570 abstract "The key to maritime surveillance is an accurate and real-time update of the current traffic situation.Although the Automatic Identification System (AIS) has greatly improved the traffic situation assessmentover the past years, it has shown to be error-prone and vulnerable to spoofing or intentional misuse. Toobtain a more reliable picture of a vessel’s motion this work proposes the fusion of AIS and Radar datain a loosely coupled architecture. For that reason, an Interacting Multiple Model (IMM) Multi SensorProbabilistic Data Association (PDA) filter was designed not only to fuse measurements from differentsources, but also to best capture the different dynamic states of a single vessel. In the IMM two UnscentedKalman Filters (UKFs) run in parallel and interact with each other, each implementing a different dynamicmodel, the CV and CTRV, respectively. Each UKF is conditioned on asynchronous measurements obtainedfrom either AIS or Radar. In case of the latter, measurements of a target candidate may also originatefrom clutter, not from the target itself. The PDA filtering approach not only associates these measurementsto the actual target state but also acts as innovation gate for faulty AIS position updates. A standard blobdetection algorithm was implemented and tuned for extracting target candidates in range and bearingfrom Radar images. To show the benefits of the proposed scheme a dedicated measurement campaignwas performed in the Baltic Sea with a stationary ship monitoring a highly manoeuvring target vessel.With the proposed approach not only short term AIS induced errors can be detected and rejected but whatmay also become observable is suspicious AIS behaviour including anomalous position data or mutedtransponders." @default.
- W3157871570 created "2021-05-10" @default.
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- W3157871570 date "2016-10-01" @default.
- W3157871570 modified "2023-09-24" @default.
- W3157871570 title "Improving the Maritime Traffic Situation Assessment for a Single Target in a Multisensor Environment" @default.
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