Application of Adaptive Extended Kalman Filter for Tracking a Moving Target

Object tracking is a very important part of precise guidance system.Aiming at moving target track problem,based on to building the moving model,the paper introduces Kalman filtering algorithm to do the research of tracking simulation.Taking into account the instability and low accuracy of passive filters in bearings-only target tracking,the paper presents an adaptive extended Kalman filter suited for nonlinear observation model and linear dynamic model.Virtual noise is estimated,and errors due to linearization are dynamically compensated so that the system's observation error is reduced.The filtering theory and the algorithm are studied.Simulation results show that MPAEKF can improve the filter convergence and accuracy.