Fuzzy Correlation Algorithm for Multi-Target Fusion of Automatic Identification System and Radar

At present more and more vessels are equipped with AIS (Automatic Identification System), which is a new system used primarily as a tool for maritime safety, including vessel collision avoidance. As a means for coastal nations' Vessel Traffic Service (VTS) to get information on vessels operating near the coast, the traditional radar and the new AIS become the two sources of getting the vessels information. Therefore, the tracks fusion of AIS and radar is the key technology to be resolved in VTS. The tracks correlation is the premise and basis of tracks fusion. This paper proposed an improved method of fuzzy correlation algorithm based on the maximum membership to fuse redundant observations due to multi-sensor (such as radar and AIS) coverage in VTS. We made generous correlation decision by time and distance and obtain the targets in a fixed range, and then we made precise correlation utilizing the membership function of Cauchy-type. The simulation experiment shows the proposed fuzzy correlation algorithm is correct and stable. The result of this effort is a computational efficient and cost effective software solution to a significant system deficiency that impacts greatly on overall waterway safety.