Feature Extraction of Precession Targets Based on Feature Extraction of Precession Targets Based on Multi-aspect Micro-Doppler Fusion
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摘要: 微动特征是弹道目标识别的重要特征之一。针对锥体目标模型，提出了一种基于多视角窄带雷达网的微动参数提取方法。在详细分析锥体目标等效散射中心微多普勒变化规律的基础上，利用各散射中心之间的微多普勒相关性，结合频率补偿的方法，实现了回波多普勒谱中各散射中心对应的微多普勒曲线的匹配识别。在此基础上，构建多视角联合方程组，提取出锥体目标的进动角、底面半径、锥体高度等参数。仿真结果证明了该方法的有效性与适应性。Abstract: Micro-motion feature is one of the crucial features used for ballistic target recognition. Aiming at the model of cone-shaped target, a novel algorithm based on the multi-aspect narrowband radar network is proposed to extract the micro-motion parameters in this paper. Firstly, on the basis of analyzing the micro-Doppler change rule of the equivalent scattering centers on the precession cone-shaped target in detail, the micro-Doppler curve of each scattering center in echo Doppler spectrum is matched and identified by utilizing the correlation of the micro-Doppler among three scattering centers combined with the frequency compensation method. Then based on this, the multi-aspect associated systems of equations are established, and parameters including the precession angle, radius of undersurface and height of the cone-shaped target are extracted jointly. Finally, the simulation results are given for validating the effectiveness and adaptability of the proposed algorithms.
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Keywords:
- precession feature /
- narrowband radars /
- frequency compensation /
- Multi-aspect
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期刊类型引用(1)
1. 吴华芹. 云计算海量光纤数据的差异化调度研究. 激光杂志. 2019(01): 155-158 . 
百度学术
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