A hybrid measurement fusion algorithm for multisensor target tracking

In order to improve the target tracking consistency and the anti-jamming ability of ship-borne surveillance and fire control system, a centralized multisensor target tracking system was constructed. The system comprised a four-band radar working in frequency hopping mode, a passive infrared angular tracker, a television angular tracker, and a laser distance detector. All the sensors are mounted on the same platform. A hybrid measurement fusion algorithm is presented, which firstly compresses the measurements of the same type, and then updates the target track by using sequential multisensor probabilistic data association (MSPDA) method. Numerical simulation results show that the hybrid fusion algorithm improves the tracking accuracy significantly and requires much less computation than the sequential MSPDA method.