Target Tracking Algorithm of Radar and Infrared Sensor Based on Multi-Source Information Fusion

Nowadays, with the extensive application of interference technology, the accuracy and stability of target tracking system are facing severe challenges. In order to improve the tracking accuracy and anti-interference ability of UAV to ship targets, a multi-mode compound tracking algorithm based on multi-source information fusion is proposed. Firstly, the local estimation of radar and infrared sensor is given based on the interacting multi model unscented Kalman filter (IMM-UKF) algorithm. On this basis, the interference detection module is introduced to identify and reconstruct the interfered track. Finally, the global estimation of the track is given based on the hierarchical track fusion algorithm. The simulation results show that the algorithm can not only improve the target tracking accuracy, but also effectively improve the anti-interference ability and stability of the tracking system.