A Maneuvering Target Tracking Algorithm Based on Radar/ Infrared Sensor Neural Network Fusion

A maneuvering target tracking algorithm based on Radar / Infrared sensor neural network fusion is presented. A neural network with a Kalman filter is characterized with a nonlinear tracking filter, which enables to make fully use of the image-based additional information for maneuvering detection and keeps the simplicity of the algorithm for the part of its computation load is transferred to the neural networks. Simulation results show that the proposed algorithm has significant advantages over the common nonlinear estimation algorithms in tracking applications for its reduction of computation complexities and its improvement of calculation speed.