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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >M-correlated sweeps performance analysis of mean-level CFARprocessors in multiple target environments
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M-correlated sweeps performance analysis of mean-level CFARprocessors in multiple target environments

机译：多个目标环境中均值CFAR处理器的M相关扫描性能分析

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摘要

This paper is devoted to the detection performance evaluation of the mean-level (ML) constant false-alarm rate (CFAR) detectors processing M-correlated sweeps in the presence of interfering targets. The consecutive pulses are assumed to be fluctuating according to the Swerling I model. Exact expressions are derived for the detection probability of the conventional mean-level detector (MLD) and its modified versions under Rayleigh fluctuating target model. Performance for independent sweeps can be easily obtained by setting the sweep-to-sweep correlation coefficient equal to zero. Results are obtained for both homogeneous and nonhomogeneous background environments. It is shown that for fixed M, the relative improvement over the single sweep case increases as the correlation between sweeps decreases. For the same parameter values, the minimum MLD has the best performance in the presence of extraneous target returns among the reference noise samples
机译：本文致力于在存在干扰目标的情况下，处理与M相关的扫描的均值（ML）恒定误报率（CFAR）检测器的检测性能评估。假设连续的脉冲根据Swerling I模型而波动。在瑞利起伏目标模型下，可以得出精确的表达式来表示常规均值检测器（MLD）及其修改版本的检测概率。通过将扫描到扫描的相关系数设置为零，可以轻松获得独立扫描的性能。获得均质和非均质背景环境的结果。结果表明，对于固定的M，随着扫描之间的相关性降低，相对于单个扫描情况的相对改进增加。对于相同的参数值，在参考噪声样本中存在无关目标返回的情况下，最小MLD具有最佳性能

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