A fusion algorithm of target dynamic information for asynchronous multi-sensors

Radar and automatic identification system (AIS) are the important navigation equipment to obtain targets information in marine traffic. For obtaining more reliable and precise target information, it is necessary to develop a fusion method, where the target track correlation judgment and track fusion filtering are the key issue. In this investigation, we have proposed a target association algorithm of the radar and AIS based on the BP neural network algorithm and multi-sensor information fusion theory, and introduced the Kalman filter and particle filter to achieve the nonlinear track filter. By the simulation and analysis based on the measured data, it can be found that the algorithm will be accurately implemented the track correlation and effectively improve the track precision in this work.