An Adaptive Current Statistical Model Based on Estimation of Target Motion Parameters

Aiming at the acceleration of the maneuvering target changes uniformly, an adaptive Current Statistical (CS) model based on the estimation of the target motion parameters is proposed. Firstly, the improved CS model is derived by adding the jerk and jerk rate into the state vector, to get a more accurate estimation of the target motion state. Secondly, the distance, speed, acceleration, and jerk obtained by motion parameters estimation are also added to the model measurement. Furthermore, the changes of a jerk in adjacent cycles are compensated by adaptive updating of maneuver frequency. Finally, the filter equation of the improved CS model is introduced. The simulation results show that the proposed model can improve the accuracy of target tracking compared with the model that only measures distance and speed.