Chi-square test in adaptive Kalman filter of passive tracking

A χ² statistics test in Kalman filter for the detection of target maneuver is performed to improve the state estimates of range, speed and course in passive tracking. The filter structure accepts fundamentally two stage filter. The prefilter of time delays reduces the bias of state estimates,the second stage of filter uses the Cartesian coordinate system to filter R_x,R_y,V_x,V_y. For hardware simplicity,the filter does not require storage of pre-states except the χ²-test needing few,and does not make recurrent algorithm for searching optimal convergence. So the computation is small,and it is easy to build a machine. The computer simulation results and the real data analysis show good performance of state estimate.