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Robust adaptive radar detection in the presence of steering vector mismatches

机译:转向矢量不匹配时的鲁棒自适应雷达检测

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摘要

In this paper, we consider the problem of robust radar detection in the presence of Gaussian disturbance with unknown covariance matrix. We design and assess three new robust adaptive detectors, capable of operating in the presence of unknown discrepancies between the nominal and the actual steering vector. Remarkably the new decision rules exhibit a bounded constant false alarm rate (CFAR) behavior and allow, through the regulation of a design parameter, to trade off target sensitivity with sidelobes energy rejection. Finally, computer simulations show that the proposed detectors achieve a visible performance improvement, in many situations of practical interest, over the traditional adaptive detection algorithms, especially in the presence of severe steering vector mismatches.
机译:在本文中,我们考虑了存在未知协方差矩阵的高斯扰动情况下的鲁棒雷达检测问题。我们设计和评估了三个新的鲁棒自适应检测器,它们能够在标称和实际转向矢量之间存在未知差异的情况下运行。值得注意的是,新的决策规则表现出有限的恒定误报率(CFAR)行为,并允许通过设计参数的调节来权衡目标灵敏度与旁瓣能量抑制。最后,计算机仿真表明,在许多实际感兴趣的情况下,与传统的自适应检测算法相比,所提出的检测器在可见的性能上有所改善,尤其是在存在严重的转向矢量失配的情况下。

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