基于低轨星网的多目标协同跟踪滤波技术  

Cooperative tracking filtering technology of multi-target based on low orbit satellite constellation

作　　者：翟光[1] 王妍欣 孙一勇 ZHAI Guang;WANG Yanxin;SUN Yiyong(School of Aerospace Engineering,Beijing Institution of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学宇航学院,北京100081

出　　处：《系统工程与电子技术》2022年第6期1957-1967,共11页Systems Engineering and Electronics

摘　　要：低轨高密度星网因其覆盖范围广、能够对弹道目标进行全程跟踪而受到广泛的重视。针对低轨星网对多弹道目标协同跟踪问题,提出一种基于卡方分布和无迹卡尔曼滤波(unscented Kalman filter,UKF)的多目标协同跟踪滤波算法。该方法首先在卡方分布的假设下,设计了一种基于测量平面的数据关联指标函数,实现量测值的分配;在此基础上采用变结构滤波框架对多弹道目标进行状态更新;最后给出了多目标状态估计性能的评估指标。数值仿真实验证明,所提算法可以有效地实现多目标在测量平面上的数据关联,并以较少的计算量对多目标进行准确估计。The low orbit and high density satellite constellation attracts increasing attention due to its wide coverage and its capability of tracking ballistic targets throughout their traces.To cope with the problem of multiple ballistic targets cooperative tracking,this paper proposes a multi-target cooperative tracking filter based on Chi-square distribution and unscented Kalman filter(UKF).Under the assumption of a Chi-square distribution,this paper develops an indicator function of data association on the measurement plane to assign measurements.And based on the assignment,the variable filter structure is adopted to update the states of multi-target.Finally,the evaluation index of multi-target state estimation performance is given.The numerical simulations show that the algorithm proposed in this paper can effectively realize data association on measurement plane and estimate the state of multiple maneuvering targets(MTT)accurately with less computational load.

关 键 词：机动多目标跟踪 数据关联 无迹卡尔曼滤波 卡方分布 

分 类 号：TN96[电子电信—信号与信息处理]