摘要
针对批处理关联方式对航迹整体信息利用不足以及现有抗差算法无法实现大系统误差下的关联等问题,提出一种基于迭代离散度序贯检测的航迹抗差关联算法。该算法首先引入迭代离散度作为关联统计量,并根据基于误差重构的随机量测量推导得到不同时刻离散度的概率分布;然后根据检测终点的不同设计了两种关联判定准则,在不同判定准则下进行离散度的序贯检测实现航迹的抗差关联。实验结果表明,算法在密集目标、大系统误差等复杂场景下均有较高的正确关联率,并且较常规算法关联速度提升明显。
Aiming at the shortcoming of the batch correlation method’s insufficient utilization of the overall track information and the existing anti-bias algorithm’s inability to deal with the correlation under large system errors, an anti-bias track association algorithm based on sequential detection of iterative discrete degree is proposed. Firstly, the iterative discrete degree is introduced as the correlation statistic, and the probability distribution of discrete degree at different times is derived from the random measurement based on error reconstruction. Then two correlation criteria are designed according to the different detection endpoints, and the sequential detection of discrete degree is carried out under different criteria to realize the anti-bias correlation of tracks. Experimental results show that the algorithm has a high correct correlation rate in complex scenes such as dense targets and large systematic errors, and the correlation speed is significantly improved compared with the conventional algorithm.
作者
关欣
国佳恩
GUAN Xin;GUO Jia’en(Naval Aviation University,Yantai 264001,China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2022年第8期2498-2505,共8页
Systems Engineering and Electronics
基金
国防科技卓越青年人才基金(2017-JCJQ-ZQ-003)
泰山学者工程专项经费(ts201712072)资助课题。
关键词
航迹关联
序贯检测
系统误差
离散度
track association
sequential detection
systematic error
discrete degree
