Application of Extended Kalman Algorithms in Nonlinear Target Tracking of Airborne Laser Communication and Optical Platform

摘要

In order to balance the design of airborne laser communication and photoelectric tracking, and effectively improve the tracking accuracy of the system, in this study, an integrated system of airborne laser communication and photoelectric tracking is proposed. The extended state Kalman filter (EKF) is used to predict the target state, so as to improve the tracking accuracy of the system. According to the airborne system model, the linear target model and the nonlinear observation model are selected. The tracking coordinate system is selected as the hybrid coordinate system, and the target motion model is analyzed. When the airborne end communicates with the moving target, this study proposes to use the passive detection to achieve the coarse tracking function. Since the use of laser ranging will lead to power waste, this study will propose an error-corrected extended Kalman prediction algorithm (Error Correct-Extend Karman Filter, EC-EKF), to achieve fine tracking of the target. The simulation results show that the EC-EKF proposed in this study can effectively reduce the nonlinear tracking error and improve the accuracy of the target position error, which is in line with the accuracy requirements of airborne laser communication.