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Target detection with linear and kernel subspaces matching in the presence of strong clutter

机译:在强杂波存在下,通过线性和核子空间匹配进行目标检测

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摘要

This paper proposes potential approaches to detect the weak target in the presence of strong disturbance. The disturbance consists of strong clutter and white Gaussian noise. The target and clutter are assumed to lie in the corresponding subspaces. The algorithms of subspace matching in the linear and kernel subspaces are derived respectively. The leading eigenvector matching that is the subspace with rank one is investigated as well. The simulation is done for two sensor arrays based on the characteristics of the clutter environment. The results from the simulation show the potential and promising uses of the proposed algorithms to detect the weak target.
机译:本文提出了在强干扰情况下检测弱目标的潜在方法。干扰包括强烈的杂波和高斯白噪声。假定目标和杂波位于相应的子空间中。分别推导了线性子空间和核子空间中的子空间匹配算法。还研究了前导特征向量匹配,该匹配是具有等级1的子空间。基于混乱环境的特征,对两个传感器阵列进行了仿真。仿真结果表明,该算法在检测弱目标方面具有潜在的应用前景。

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