Fuzzy Functional Dependencies as a Method of Choice for Fusion of AIS and OTHR Data.

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ID: 94330
2019
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Abstract
Maritime situational awareness at over-the-horizon (OTH) distances in exclusive economic zones can be achieved by deploying networks of high-frequency OTH radars (HF-OTHR) in coastal countries along with exploiting automatic identification system (AIS) data. In some regions the reception of AIS messages can be unreliable and with high latency. This leads to difficulties in properly associating AIS data to OTHR tracks. Long history records about the previous whereabouts of vessels based on both OTHR tracks and AIS data can be maintained in order to increase the chances of fusion. If the quantity of data increases significantly, data cleaning can be done in order to minimize system requirements. This process is performed prior to fusing AIS data and observed OTHR tracks. In this paper, we use fuzzy functional dependencies (FFDs) in the context of data fusion from AIS and OTHR sources. The fuzzy logic approach has been shown to be a promising tool for handling data uncertainty from different sensors. The proposed method is experimentally evaluated for fusing AIS data and the target tracks provided by the OTHR installed in the Gulf of Guinea.
Reference Key
mohamed-mostafa2019fuzzysensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Mohamed Mostafa, Medhat Abdel Rahman;Vucetic, Miljan;Stojkovic, Nikola;Lekić, Nikola;Makarov, Aleksej;
Journal sensors
Year 2019
DOI
E5166
URL
Keywords
data fusion maritime surveillance ais hf-oth radar fuzzy functional dependencies radar tracking authentication security protocol industry 4.0 industrial internet of things (iiot)

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