基于高分辨谱估计的雷达目标分类方法

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中图分类号：TN959.1 文献标志码：A DOI：10.12305/j.issn.1001-506X.2025.07.08

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 highresolution 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 velocityinterval 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 clasification algorithm with high-resolution spectrum estimation has a significant classification effect.

Keywords：high-resolution spectrum estimation；energy distribution characteristic；velocity interval； back-propagation （BP） neural network

0 引言

雷达目标分类识别在国防军事领域和生产生活中具有重要意义[1-2]，分类结果的好坏取决于特征提取是否稳健有效。（剩余14714字）