基于高分辨谱估计的雷达目标分类方法

doi:10.12305/j.issn.1001-506X.2025.07.08

Abstract

Abstract:

To address the classification problem of ground and low-altitude moving targets such as people, vehicles, and unmanned aerial vehicles using high-resolution spectrum estimation in conventional narrowband radar system, the energy distribution characteristics of the echo signal spectrum are extracted through high-resolution spectral estimation firstly. Then, the time domain and frequency domain characteristics of the echo signal are analyzed, and the target speed, radar cross section (RCS), time domain waveform entropy, amplitude relative value, and frequency domain variance are extracted. According to the actual motion of the target, the velocity interval is divided, and a corresponding back-propagation (BP) neural network model is designed. Finally, the experiment based on the measured radar echo data proves that the target classification algorithm with high-resolution spectrum estimation has a significant classification effect.

Key words: high-resolution spectrum estimation, energy distribution characteristic, velocity interval, back-propagation (BP) neural network

CLC Number:

TN959.1

Mengze ZHANG, Liyu TIAN. Radar target classification method based on high resolution spectral estimation[J]. Systems Engineering and Electronics, 2025, 47(7): 2146-2153.

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References 32

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目标类别	速度分布范围/(m/s)	距离分布范围/m
人	1~5	200~20 000
车	1~22	200~20 000
无人机	1~15	200~20 000

目标类别	低速区	高速区	样本总数
人	18 848	—	18 848
车	12 118	6 844	18 962
无人机	16 172	16 668	32 840

区域	测试集识别率
区域	特征谱法	FFT法	MUSIC谱估计	AR模型谱估计
低速区	92.73	94.55	92.81	95.21
高速区	95.79	97.21	96.25	97.92

区域	测试集识别率
区域	17维能量分布特征	5维时域和频域特征	22维组合特征
低速区	88.64	91.35	95.21
高速区	91.17	96.08	97.92

目标类型	人	车	无人机	测试集识别率/%	总识别率/%
人	3 590	122	60	95.17	95.21
车	95	2 175	66	93.11	95.21
无人机	59	45	3 132	96.78	95.21

Radar target classification method based on high resolution spectral estimation

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