一种基于时频分析的窄带雷达飞机目标分类特征提取方法

赵越; 陈之纯; 纠博; 张磊; 刘宏伟; 李真芳

doi:10.11999/JEIT161204

一种基于时频分析的窄带雷达飞机目标分类特征提取方法

doi: 10.11999/JEIT161204

基金项目:

国家自然科学基金(61671351)，国家杰出青年科学基金(61525105)

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- 文章访问数: 1421
- HTML全文浏览量: 138
- PDF下载量: 258
- 被引次数: 0
出版历程
- 收稿日期: 2016-11-08
- 修回日期: 2017-06-05
- 刊出日期: 2017-09-19

Narrowband Aircraft Targets Feature Extraction and Classification Based on Time-frequency Analysis

Funds:

The National Natural Science Foundation of China (61671351), The National Science Fund for Distinguished Young Scholars (61525105)

摘要

摘要: 针对低信噪比情况下窄带雷达目标分类问题，该文提出基于时频分析的窄带雷达飞机目标分类特征提取方法。该方法利用喷气式飞机、螺旋桨飞机和直升机3类目标调制周期的差异，提取时频谱域的熵值变化特性，并给出时频分析中窗函数长度的优化选择方法。基于仿真和实测数据的实验结果表明，该文方法可以在低信噪比情况下显著提升飞机目标正确分类概率。
- 目标分类 /
- 时频分析 /
- 特征提取 /
- 低信噪比 /
- 熵值
Abstract: A new feature extraction method based on time-frequency analysis is proposed for aircraft targets classification under low signal-to-noise ratio. This method uses the variances of time-domain modulation periods of jet aircraft, propeller aircraft and helicopter to extract the variation of entropy in the time-frequency domain and gives a way to select optimal window lengths. Experimental result based on simulated data and measured data demonstrates that the proposed method can significantly improve the classification probability of aircraft targets under low signal-to-noise ratio.
- Targets classification /
- Time-frequency analysis /
- Feature extraction /
- Low signal-to-noise ratio /
- Entropy

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参考文献(25)

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