稀疏分解在海杂波中微动目标检测中的应用

Xiaolong Chen, Yong Chai, F.Q. Cai, J. Guan
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引用次数: 4

摘要

介绍了稀疏分解原理,提出了一种在低信杂比环境下检测和提取海杂波中微运动目标的算法。首先,建立了微动目标雷达回波的三维模型,包括三维旋转运动(俯仰、横滚和偏航运动);然后,根据m-D信号的形式,提出了基于匹配跟踪稀疏分解的啁啾字典检测算法。采用分级迭代法,计算速度快。最后,利用智能像素处理雷达数据集进行了仿真,验证了该方法的有效性,并优于常用的基于傅里叶变换字典的检测器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of the sparse decomposition to micromotion target detection embedded in sea clutter
The sparse decomposition principle is introduced and a detection algorithm of target with micro-motion embedded in sea clutter is proposed, which can detect and extract micro-Doppler (m-D) signals in low signal-to-clutter ratio environment. Firstly, the three dimensional model of radar echo from micro-motion target is established including the 3-D rotated movements (pitch, roll, and yaw movements). Then, the detection algorithm based on matching pursuit sparse decomposition is proposed with chirp dictionary according to the form of m-D signals. The grading iterative method is employed for fast computation. In the end, simulations with dataset from the intelligent pixel processing radar verify the effectiveness as well as superiority over the commonly used detector based on Fourier transform dictionary.
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