基于微多普勒特征的地面目标分类

李彦兵; 杜兰; 刘宏伟; 丁苏颖; 关永胜

doi:10.3724/SP.J.1146.2010.00128

基于微多普勒特征的地面目标分类

doi: 10.3724/SP.J.1146.2010.00128

基金项目:

国家自然科学基金(60772140，60901067)和中央高校基本科研业务费专项资金联合资助课题

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出版历程
- 收稿日期: 2010-02-02
- 修回日期: 2010-07-16
- 刊出日期: 2010-12-19

Ground Targets Classification Based on Micro-Doppler Effect

摘要

摘要: 轮式履带式车辆目标分类是低分辨雷达地面目标识别研究领域的一个难点。该文基于微多普勒效应原理建立了轮式履带式车辆的雷达回波模型，针对轮式履带式车辆微多普勒调制的不同，提出了一种基于CLEAN算法的特征提取方法，提取了一种描述目标多普勒谱能量分布的能量比特征。基于实测数据使用相关向量机(RVM)和支持向量机(SVM)的识别结果表明该特征具有较好的识别性能，同时对目标速度具有稳健性。
- 雷达目标识别 /
- 微多普勒 /
- CLEAN算法 /
- 相关向量机 /
- 支持向量机
Abstract: Classification of track vehicle and wheel vehicle by using low-resolution radar echo is a challenging problem in radar ground target automatic classification community. This paper establishes an echo signal model for track vehicle and wheel vehicle based on micro-doppler effect. According to the echo signal model, a new feature extraction method is proposed by using the CLEAN algorithm. The feature reveals the energy distribution of the target doppler spectrum. The measured data results based on Relevance Vector Machine (RVM) and Support Vector Machine (SVM) show the proposed feature can not only achieve good classification performance, but also be robust to the target velocity.
- Radar automatic target recognition /
- Micro-Doppler effect /
- CLEAN algorithm /
- Relevance Vector Machine (RVM) /
- Support Vector Machine (SVM)

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参考文献(1)

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