Tracking methods of high speed strong maneuvering targets in near space

In order to alleviate the model-mismatching and improve tracking precision of high speed strong maneuvering targets in near space, a new strong tracking filter algorithm with improved jerk model is proposed. The improved jerk model, in which the acceleration is assumed to be an exponential-correlated random process with non-zero mean, is used in the paper. Moreover, a fading factor is introduced in extended kalman filter tracking which can adjust covariance matrix adaptively and improve state estimation of the maneuvering target. Finally, the simulation results show that the algorithm improves the tracking performance of the high speed strong maneuvering targets in near space.