关键,
董云龙
海军航空大学信息融合研究所 烟台 264001
基金项目:国家自然科学基金(61401495, 61471382, 61501487, 61531020, U1633122)，山东省自然科学基金(2015ZRA06052)，航空科学基金(20150184003, 20162084005, 20162084006)和“泰山****”建设工程专项经费资助
详细信息
作者简介:李保珠：男，1989年生，博士生，研究方向为雷达数据处理、航迹关联和误差配准等
关键：男，1968年生，教授，博士生导师，研究方向为雷达目标检测与跟踪与识别、海上目标信息感知与融合
董云龙：男，1974年生，博士，副教授，研究方向为雷达目标组网检测等
通讯作者:李保珠 libaozhu1324@163.com
中图分类号:TN953计量
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被引次数:0
出版历程
收稿日期:2018-03-30
修回日期:2018-07-24
网络出版日期:2018-08-06
刊出日期:2019-01-01
Anti-bias Track Association Algorithm of Radar and Electronic Support Measurements Based on Track Vectors Detection
Baozhu LI,,Jian GUAN,
Yunlong DONG
Institute of Information Fusion, Naval Aviation University, Yantai 264001, China
Funds:The National Natural Science Foundation of China (61401495, 61471382, 61501487, 61531020, U1633122), The Natural Science Foundation of Shandong Province (2015ZRA06052), The Aeronautical Science Foundation of China (20150184003, 20162084005, 20162084006), The Special Funds of Taishan Scholars Construction Engineering
摘要
摘要:针对雷达与电子支援设施(ESM)存在系统误差、上报目标不完全一致等复杂场景下目标航迹关联问题，该文基于高斯随机矢量统计特性，提出一种基于航迹矢量检测的雷达与ESM航迹抗差关联算法。首先在修正极坐标系(MPC)下推导目标状态估计分解方程，采用真实状态对消的方法得到航迹矢量，为剔除大部分非同源目标航迹，构建方位角变化率-距离变化率与距离比(ITG)统计量进行粗关联，然后采用基于航迹矢量
关键词:航迹关联/
系统误差/
雷达/
电子支援设施/
航迹矢量/
修正极坐标系
Abstract:To address track-to-track association problem of radar and Electronic Support Measurements (ESM) in the presence of sensor biases and different targets reported by different sensors, an anti-bias track-to-track association algorithm based on track vectors detection is proposed according to the statistical characteristics of Gaussian random vectors. The state estimation decomposition equation is firstly derived in the Modified Polar Coordinates (MPC). The track vectors are obtained by the real state cancellation method. Second, In order to eliminate most non-homologous target tracks, the rough association is performed according to the features of the azimuthal rate and Inverse-Time-to-Go (ITG). Finally, the track-to-track association of radar and ESM is extracted based on track vectors chi-square distribution. The effectiveness of the proposed algorithm are verified by Monte Carlo simulation experiments in the presence of sensor biases, targets densities and detection probabilities.
Key words:Track-to-track association/
Sensor bias/
Radar/
Electronic Support Measurements (ESM)/
Track vectors/
Modified Polar Coordinates (MPC)
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