一种HRRP特征辅助的多目标JPDA算法  

A HRRP Feature-aided Multi-target JPDA Algorithm

作　　者：韩卓茜 王锋 李卓伦 李宏洋 Han Zhuoxi;Wang Feng;Li Zhuolun;Li Hongyang(School of Data and Target Engineering,PLA Strategic Support Force Information Engineering University,Zhengzhou,Henan 450001,China;School of Information System Engineering,PLA Strategic Support Force Information Engineering University,Zhengzhou,Henan 450001,China;61206 Troop,Beijing 100000,China)

机构地区：[1]中国人民解放军战略支援部队信息工程大学数据与目标工程学院,河南郑州450001 [2]中国人民解放军战略支援部队信息工程大学信息系统工程学院,河南郑州450001 [3]61206部队,北京100000

出　　处：《信号处理》2020年第10期1727-1734,共8页Journal of Signal Processing

摘　　要：针对强杂波环境下,联合概率数据关联(Joint Probabilistic Data Association,JPDA)算法的计算复杂度不能满足复杂电磁环境下数据关联的实时性要求,本文提出了一种基于高分辨一维距离像(High Resolution one-dimensional Range Profile,HRRP)特征辅助的JPDA算法。首先,计算量测与目标的HRRP特征相似度;然后利用特征相似度辅助JPDA算法完成波门搜索,减少可行事件的数量;最后使用特征相似度对可行事件的发生概率进行修正,进而修正量测与目标的关联概率。实验结果表明,本文算法提高了关联性能,同时还极大地提高了算法的实时性。For solving the problem that traditional Joint Probabilistic Data Association(JPDA)algorithm with high complexity can’t meet the real time performance of data association in complicated electromagnetic environment,a JPDA algorithm based on feature aided of high resolution one-dimensional range profile(HRRP)is proposed in this paper.Firstly,the similarity of HRRP feature is calculated between the measurement and the target.Then,the number of the feasible event is reduced with the HRRP feature similarity aided JPDA algorithm to complete the gate search.Finally,the probability of the feasible event is modified by using the HRRP feature similarity,and then modify the association probability of the measurement and the target.Simulation results show that this algorithm improves the correlation performance,and also greatly improves the real time performance of the algorithm.

关 键 词：联合概率数据关联 特征辅助 高分辨一维距离像 特征相似度 

分 类 号：TN953[电子电信—信号与信息处理]