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Optimum and mismatched detection against K-distributed plus Gaussian clutter

机译:针对K分布加高斯杂波的最佳和不匹配检测

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摘要

We derive the optimum radar receiver to detect fluctuating and non-fluctuating targets against a disturbance which is modeled as a mixture of coherent K-distributed and Gaussian-distributed clutter. In addition, thermal noise, which is always present in the radar receiver, is considered. We discuss the implementation of the optimum coherent detector, which derives from the likelihood ratio test under the assumption of perfectly known disturbance statistics, and evaluate its performance via a numerical procedure, when possible, and via Monte Carlo simulation otherwise. Moreover, we compare the performance of the optimum detector with those of two detectors which are optimum for totally Gaussian and totally K-distributed clutter respectively, when they are fed with such a mixed disturbance. We conclude that, though the optimum detector has a larger computational cost, it provides sensibly better detection performance than the mismatched detectors in a number of operational situations. Thus, there is a need to derive suboptimum target detectors against the mixture of disturbances which trade-off the detection performance and the implementation complexity.
机译:我们推导了最佳雷达接收器,以检测针对干扰的波动和非波动目标,该干扰被建模为相干K分布和高斯分布杂波的混合。另外,考虑了雷达接收机中始终存在的热噪声。我们讨论了最佳相干检测器的实现,该检测器是在完全已知的干扰统计假设下从似然比测试得出的,并在可能的情况下通过数值程序评估性能,否则通过蒙特卡洛模拟进行评估。此外,我们将最佳检测器的性能与两个检测器的性能进行了比较,这两个检测器在受到这种混合干扰的情况下分别分别对全高斯和全K分布的杂波而言是最佳的。我们得出的结论是,尽管最佳检测器具有较大的计算成本,但在许多操作情况下,与不匹配的检测器相比,它提供了明显更好的检测性能。因此,需要针对干扰的混合来导出次优目标检测器,这些干扰会折衷检测性能和实现复杂性。

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