| 摘要: |
| 针对目标密集场景下，敌我识别（Identification Friend or Foe,IFF）结果和雷达目标关联不准确的问题，提出了一种基于压缩感知理论的雷达目标关联方法。将阵列接收信号协方差矩阵向量化处理形成观测向量，以多个雷达目标方位信息为基础扩充形成多个目标方位簇，并构建基于方位簇虚拟阵列流形的观测矩阵，通过观测向量在观测矩阵上的投影判断阵列接收信号与多个雷达目标方位相关性大小，形成关联判决结果。典型场景下的仿真结果表明，该方法能够实现敌我识别结果与雷达目标的高正确率关联，在阵元数28、信噪比3 dB、雷达测向误差不超过0.2°的条件下，对方位角相差不低于0.5°的两个目标能够实现准确关联。 |
| 关键词: 雷达目标 敌我识别 目标关联 压缩感知 |
| DOI：10.20079/j.issn.1001-893x.241111003 |
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| 基金项目: |
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| A Radar Target Association Method Based on Compressed Sensing |
| YAN Shanyong |
| (Southwest China Institute of Electronic Technology,Chengdu 610036,China) |
| Abstract: |
| In response to the issue of inaccurate integration of identification friend or foe(IFF)results and radar targets in scenarios with dense targets,a radar target association method based on compressed sensing(CS)theory is proposed.The covariance matrix of the received signal by array is vectorized for observation vector formation.Multiple radar target azimuth information is used to expand into several target azimuth clusters.Based on these azimuth clusters,a virtual array beamforming observatory matrix is constructed.By projecting the observation vector onto the observatory matrix,the degree of correlation between the array received signal and multiple radar target azimuths is determined,forming an association decision result.Simulation results under typical scenarios indicate that this method can achieve high-accuracy association between IFF results and radar targets.Specifically,under conditions of 28 antenna elements,a signal-to-noise ratio of 3 dB,and a radar bearing error less than 0.2°,it can accurately associate two targets with an angular difference of at least 0.5°. |
| Key words: radar target identification friend and foe target associated compressed sensing |
