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首页> 外文期刊>WSEAS Transactions on Signal Processing >Parametric Rao Test for Multichannel Adaptive Generalized Detector
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Parametric Rao Test for Multichannel Adaptive Generalized Detector

机译：多通道自适应广义检测器的参数Rao检验

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摘要

The parametric Rao test for multichannel signal detection by the adaptive generalized detector (GD) constructed based on the generalized approach to signal processing in noise is derived by modeling the disturbance signal as a multichannel autoregressive process. The parametric Rao test takes a form identical to that of parametric GD for space-time adaptive processing in airborne surveillance radar systems and other similar applications. The equivalence offers new in-sights into the performance and implementation of the GD. Specifically, the Rao/GD is an asymptotically (in the case of large samples) parametric generalized likelihood ratio test generalized detector (GLRT GD) due to an asymptotic equivalence between the Rao test and the GLRT/GD. The asymptotic distribution of the Rao/GD test statistic is obtained in the closed form, which follows an exponential distribution under the null hypothesis (the target return signal is absent) and, respectively, a non-central Chi-squared distribution with two degrees of freedom under the alternative hypothesis (the target return signal is present). The noncentrality parameter of noncentral Chi-squared distribution is determined by the output signal-to-interference-plus-noise ratio of a temporal whitening filter. Since the asymptotic distribution at the null hypothesis is independent of the unknown parameters, the Rao/GD asymptotically achieves constant false alarm rate (CFAR) GD. Numerical results show that these results are superior in predicting the performance of the parametric adaptive matched filter even with moderate data support.
机译：通过将干扰信号建模为多通道自回归过程，得出了基于基于噪声中信号处理的通用方法构造的自适应通用检测器（GD）进行多通道信号检测的参数Rao测试。参数Rao测试采用与参数GD相同的形式，用于机载监视雷达系统和其他类似应用中的时空自适应处理。等效性为GD的性能和实施提供了新的见解。具体而言，由于Rao检验和GLRT / GD之间的渐近等价性，Rao / GD是渐近（在大样本情况下）参数化广义似然比检验广义检测器（GLRT GD）。 Rao / GD检验统计量的渐近分布以封闭形式获得，它遵循零假设（不存在目标返回信号）下的指数分布以及分别具有两个度数的非中心卡方分布。选择假设下的自由度（存在目标返回信号）。非中心卡方分布的非中心参数由时间白化滤波器的输出信号干扰加噪声比确定。由于零假设下的渐近分布与未知参数无关，因此Rao / GD渐近实现恒定的误报率（CFAR）GD。数值结果表明，即使有中等程度的数据支持，这些结果在预测参数自适应匹配滤波器的性能方面也表现出色。

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