Information fusion algorithm for target tracking of composite seeker
Yumeng Han, Xiaohong Jia · 2016
On the basis of the characteristics for the millimeter wave radar and infrared imaging composite seeker, an information fusion algorithm has been designed based on interactive multiple model particle filter for the radar and infrared composite seeker. The interactive multiple model is combined with the particle filter algorithm. In this algorithm, the sub-optimal filter of the interactive multiple model (IMM) has been replaced by the particle filter algorithm. And it has efficiently solved the tracking problem for the maneuvering target under the conditions which are nonlinear and non-Gaussian. The simulation results show that the interactive multiple model particle filter algorithm has higher performance than interactive multiple model algorithm based extended Kalman filter. And this algorithm can be very sensitive to the change of the target maneuvering and can effectively improve the target tracking accuracy.