基于锚定思想的新型雷达与ESM异步关联算法

doi:10.12305/j.issn.1001-506X.2026.03.11

摘要/Abstract

摘要：

针对同地配置的雷达与电子支援措施存在数据率不等、航迹异步、系统误差等复杂状况，提出一种异步锚定配对的关联算法。首先，定义参考序列和时域处理窗，经动态去偏除杂后加权生成异步锚定配对点。然后，提出系统误差背景下的同地配置雷达与电子支援措施的参数区间化表示方法，给出相离度矩阵求解方法，利用Jonker-Volgenant算法和经典分配算法进行关联判定。最后，给出该算法推广至同地配置的多传感器多目标场景的适用性分析。所提算法能够优化异步数据结构，减小数据冗余度，避免异常数据干扰和区间泛化问题。仿真结果表明，所提算法在异步非等速率航迹关联中具有较高的关联正确率，在多目标不规则运动复杂环境下仍具有一定的稳定性。

关键词: 同地配置, 雷达, 电子支援措施, 异步锚定配对, 相离度矩阵

Abstract:

Considering the complex situations such as unequal data rates, asynchronous tracks, and systematic errors of the co-located radar and electronic support measures（ESM）, an asynchronous anchoring and pairing association algorithm is proposed. Initially, the reference sequence and the time domain processing window are defined, dynamically remove bias and clutter, and weight to generate asynchronous anchor pairing points. Secondly, a parameter interval representation method for co-located radar and ESM under the background of system error is proposed, and a method for solving the phase separation matrix is given. The Jonker-Volgenant algorithm and the classical allocation algorithm are used for correlation determination. Finally, an analysis of the applicability of the algorithm extends to multi-sensor and multi-target scenarios is provided. The proposed algorithm can optimize asynchronous data structures, reduce data redundancy and avoid interference from abnormal data and issues of interval generalization. The simulation results show that the proposed algorithm has a high association accuracy rate in the association of asynchronous non-equal-rate tracks, and has certain stability in complex environments with multi-target and irregular movements.

Key words: co-location, radar, electronic support measures (ESM), asynchronous anchoring and pairing, dissimilarity matrix

中图分类号:

V 271.4

黄治军, 衣晓, 关欣. 基于锚定思想的新型雷达与ESM异步关联算法[J]. 系统工程与电子技术, 2026, 48(3): 835-845.

Zhijun HUANG, Xiao YI, Xin GUAN. Radar and ESM asynchronous association algorithm based on anchoring concept[J]. Systems Engineering and Electronics, 2026, 48(3): 835-845.

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误差	关联正确率
误差	本文算法	传统算法
$ \nu _{\theta }^{s}={0.1}^{\circ },\nu _{\theta }^{w}={1}^{\circ } $	0.935 0	0.875 0
$ \nu _{\theta }^{s}={0.1}^{\circ },\nu _{\theta }^{w}={1.5}^{\circ } $	0.928 5	0.856 0
$ \nu _{\theta }^{s}={0.1}^{\circ },\nu _{\theta }^{w}={2}^{\circ } $	0.914 0	0.814 5
$ \nu _{\theta }^{s}={0.2}^{\circ },\nu _{\theta }^{w}={1}^{\circ } $	0.936 0	0.875 0
$ \nu _{\theta }^{s}={0.2}^{\circ },\nu _{\theta }^{w}={1.5}^{\circ } $	0.928 0	0.846 5
$ \nu _{\theta }^{s}={0.2}^{\circ },\nu _{\theta }^{w}={2}^{\circ } $	0.911 0	0.840 0
$ \nu _{\theta }^{s}={0.5}^{\circ },\nu _{\theta }^{w}={1}^{\circ } $	0.931 0	0.858 0
$ \nu _{\theta }^{s}={0.5}^{\circ },\nu _{\theta }^{w}={1.5}^{\circ } $	0.917 0	0.835 0
$ \nu _{\theta }^{s}={0.5}^{\circ },\nu _{\theta }^{w}={2}^{\circ } $	0.902 0	0.828 0

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