Measurement level AIS/Radar Fusion for Maritime Surveillance

Using the Automatic Identification System (AIS) ships identify themselves intermittently by broadcasting their location information. However, traditionally radars are used as the primary source of surveillance and AIS is considered as a supplement with a little interaction between these data sets. The data from AIS is much more accurate than radar data with practically no false alarms. But unlike the radar data, the AIS measurements arrive unpredictably, depending on the type and behavior of a ship. The AIS data includes target IDs that can be associated to initialized tracks. In multitarget maritime surveillance environment, for some targets the revisit interval form the AIS could be very large. In addition, the revisit intervals for various targets can be different. In this paper, we proposed a joint probabilistic data association based tracking algorithm that addresses the aforementioned issues to fuse the radar measurements with AIS data. Multiple AIS IDs are assigned to a track, with probabilities updated by both AIS and radar measurements to resolve the ambiguity in the AIS ID source. Experimental results based on simulated data demonstrate the performance the proposed technique.