An improved algorithm for multi-factor fuzzy correlation
Chang Liu, Zhenyu Na, Xin Zhang
School of Information Science and Technology, Dalian Maritime University, Dalian 116026, Liaoning, China
As a means for Vessel Traffic Service (VTS) to oversee the vessels, the traditional radar and the new navigation method of Automatic Identification System (AIS) are the two sources of getting the vessels' information. Tracks Fusion of the data received from these two sensors becomes the fundamental problem to be resolved in VTS. The tracks correlation is the premise and basis of the tracks fusion. This paper proposed an improved algorithm of multi-factor integrated fuzzy correlation based on the least square-time interpolation. We make generous correlation decision of distance and achieve the targets set in a fixed range, and then after time correction based on the least square-time interpolation we get the correlated tracks set and make fuzzy correlation used the membership function of normal distribution. The simulation experiment shows the proposed fuzzy correlation algorithm is more precise and the data are more close to the actual data of the vessel. The result of this effort can become an efficient method that impacts greatly on the vessel traffic management.