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Maneuvering target tracking algorithm based on current statistical model in three dimensional space

This paper is mainly to solve the problems associated with maneuvering target tracking based current statistical model in three dimensional space. Firstly, a three-dimensional model of the nine state variables is presented. Then adaptive Kalman filtering algorithm is designed with the motor acceleration data mean and variance. Finally, A simulation about the adaptive Kalman filtering put forward by this thesis and the direct calculation method is given, which aim at the maneuvering target in three-dimension. The results show the good performances such as better target position, velocity and acceleration estimates brought by the proposed approach by presenting and discussing the simulation results.