低信噪比条件下直升机微动特征提取方法

张朝伟; 夏赛强; 杨军; 刘建卫; 徐颖鑫

引用本文:	张朝伟，夏赛强，杨军，刘建卫，徐颖鑫. 低信噪比条件下直升机微动特征提取方法[J]. 雷达科学与技术, 2021, 19(6): 689-696.[点击复制]
	ZHANG Chaowei, XIA Saiqiang, YANG Jun, LIU Jianwei, XU Yingxin. An Extraction Method for Helicopter Micro-Motion Features Under Low SNR[J]. Radar Science and Technology, 2021, 19(6): 689-696.[点击复制]

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低信噪比条件下直升机微动特征提取方法
张朝伟，夏赛强，杨军，刘建卫，徐颖鑫
空军预警学院，湖北武汉430019

摘要:

直升机旋翼转动产生的微多普勒调制能够反映其微动特性，准确估计出目标的叶片数量、旋翼长度和转动频率对直升机的识别具有重要意义。本文针对窄带脉冲体制雷达，提出一种低信噪比条件下的旋翼直升机微动特征快速高精度提取方法，推导了微动特征参数之间的内在联系，在时频域通过对时频图幅值进行积累获取目标闪烁参数，并将其作为先验信息对稀疏字典进行降维处理，降低正交匹配追踪算法的运算量，提高了微动特征参数的估计精度，在低信噪比条件下具有较好的鲁棒性，仿真和实验结果验证了方法的有效性。

关键词: 微多普勒时频图幅值积累正交匹配追踪特征提取

DOI：DOI:10.3969/j.issn.1672-2337.2021.06.007

分类号:TN958.3

基金项目:国家自然科学基金(No.61671469)；军内重点科研项目（No.KJ20201A020301）

An Extraction Method for Helicopter Micro-Motion Features Under Low SNR

ZHANG Chaowei, XIA Saiqiang, YANG Jun, LIU Jianwei, XU Yingxin

Air Force Early Warning Academy, Wuhan 430019, China

Abstract:

The micro-Doppler modulation generated by the rotor rotation of helicopter can reflect the micro-motion characteristics. Accurately estimating the number of blades, rotor length and rotation frequency is of great significance for helicopter identification. Aiming at the narrow-band pulse radar, this paper proposes a fast and high-precision extraction method for the micro-motion features of helicopter under the condition of low SNR. The internal relationship between the micro-motion parameters is deduced. The amplitude of the time-frequency map is accumulated in the time-frequency domain to obtain target flicker parameters as the prior information to reduce the dimensionality of the sparse dictionary. The proposed method can reduce the computational complexity of the orthogonal matching pursuit (OMP) algorithm, improve the estimation accuracy of the micro-motion features, and have better robustness under the condition of low SNR. The validity of the method is verified by simulation and experiment results.

Key words: micro-Doppler time-frequency diagram amplitude accumulation orthogonal matching pursuit (OMP) feature extraction