一种参数自适应变化的强机动目标跟踪算法

A strong maneuvering target tracking algorithm with adaptively changed parameters

针对强机动目标跟踪模型难以准确匹配以及跟踪滤波器容易发散的问题,提出一种基于参数自适应变化的强机动目标跟踪算法。对“当前”统计Jerk(improved Jerk model based on current statistics,CS-Jerk)跟踪模型中的机动频率及加速度变化率的极大值进行自适应处理,同时将强跟踪滤波器(strong tracking filter,STF)中的单重时变渐消因子调整为自适应变化的多重时变渐消因子,从而实现对强机动目标更高精度的跟踪。仿真实验结果表明,该算法提高了对强机动目标的跟踪精度。

Aiming at the problem that the strong maneuvering target tracking model is difficult to match accurately and the tracking filter is easy to diverge,a strong maneuvering target tracking algorithm based on adaptively changed parameters is proposed.In this algorithm,the maneuver frequency and maximum rate of acceleration change in the CS-Jerk tracking model are adaptively processed,and meanwhile,the single time-varying fading factor in Strong Tracking Filter(STF)is set as multiple time-varying fading factors that can vary adaptively.Compared with the traditional counterpart,higher precision tracking of strong maneuvering targets can be achieved by the proposed algorithm.The simulation results show that the algorithm improves the tracking accuracy of strong maneuvering targets.