一种基于IMMPDA-UKF的机动目标跟踪算法

A maneuvering target tracking algorithm based on IMMPDA-UKF

为了实现对在航捷点附近做机动运动目标的精确跟踪,提出采用不敏卡尔曼滤波(UKF)作为底层的滤波算法,解算出方位和俯仰的角度变化率,通过角度变化率解算出目标的切向速度,在过航捷时建立新的跟踪模型,将切向速度扩充到观测方程中,并结合交互多模型概率数据关联算法(IMMPDA)实现对过航捷机动目标的跟踪。仿真结果表明,该算法跟踪精度高,在航捷点附近无论是转弯机动还是加速运动,都可以保持对目标的持续跟踪,稳定性较高,可以直接应用于工程实践。

In order to achieve the accurate tracking maneuvering target at approach point, proposed an bottom filtering algorithm using unscend kalman filter（UKF）. The algorithm can calculate the azimuth and elevation angle changing rate, then can calculate the target tangential velocity. The new model of the maneuvering target is established when the target at approach point, tangential velocity would be extended to the observation equation, combined with the interacting multiple model probabilistic data association algorithm （IMMPDA） can achieve the accurate tracking maneuvering target at approach point. The simulation results show that the algorithm has high tracking accuracy and high stability, at approach point , both turn maneuver or accelerated motion Can keep continuous tracking of targets. The algorithm can he directly applied to engineering practice.