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Polarimetric adaptive detection of range-distributed targets

机译:对距离分布目标的极化自适应检测

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We address the problem of polarimetric adaptive detection of range-spread targets in Gaussian noise with unknown covariance matrix. At the design stage, we model the target echo from each polarimetric channel as a deterministic signal known up to a scaling factor (possibly varying from cell to cell), which accounts for the polarimetric scattering properties of the target. We first show the failure of the generalized likelihood ratio test (GLRT) procedure to deal with this kind of problem, and thus, we propose a fully adaptive detector based on the method of sieves. We also derive the analytical expression for the probability of false alarm and show that the newly introduced receiver can be made bounded constant false alarm rate (CFAR). Finally, we present simulation results highlighting the performance gain that can be achieved by resorting to polarization diversity in conjunction with high resolution.
机译:我们解决了对高斯噪声中具有未知协方差矩阵的距离扩展目标进行极化自适应检测的问题。在设计阶段,我们将来自每个极化通道的目标回波建模为已知的确定性信号,直至确定​​比例因子为止(可能因细胞而异),这考虑了目标的极化散射特性。我们首先说明了广义似然比检验(GLRT)程序无法解决此类问题,因此,我们提出了一种基于筛网方法的全自适应检测器。我们还推导了误报概率的解析表达式,并表明可以将新引入的接收器设为有界的恒定误报率(CFAR)。最后,我们给出了仿真结果,突出了通过结合极化分集和高分辨率可以实现的性能增益。

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