Separation of space group targets based on high-order moment function and EMD

Ying Luo, Yi-jun Chen, Hua Guan, Tao-yong Li, D. Deng
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Abstract

Space target recognition is one of the radar's significant tasks. The separation of group targets is the basis of the target recognition when several targets are within a range cell of one radar beam. In this paper, a method for group targets separation based on high-order moment function and empirical model decomposition (EMD) is proposed. The first step is deriving the high-order moment function of the target echo signal, and then processing the imaginary parts of the high-order moment function with EMD method. We can achieve the separation of group targets according to the derivational IMF from the decomposition. Simulation is given to validate the effectiveness of the proposed method.
基于高阶矩函数和EMD的空间群目标分离
空间目标识别是雷达的重要任务之一。当多个目标在同一雷达波束的距离单元内时,群目标分离是目标识别的基础。提出了一种基于高阶矩函数和经验模型分解(EMD)的群目标分离方法。首先推导目标回波信号的高阶矩函数,然后用EMD方法对高阶矩函数的虚部进行处理。我们可以根据分解得到的衍生IMF来实现群目标的分离。仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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