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The use of a generalized likelihood ratio test (GLRT) based on the late-time scattered return for target discrimination was recently presented in [1]. The performance of the GLRT was demonstrated by direct simulation with scattering data from a target library consisting of several thin-wire targets. In this paper, a numerical procedure for analytically evaluating the performance of the GLRT is presented. At the heart of this procedure is the computation of the probability density of the GLRT decision statistic. Unlike previous works that rely solely on some simulation examples to demonstrate performance, our accurate analytical results provide strong evidence of the effectiveness of the GLRT method. The resulting analysis yields a measure of the discrimination capability of the GLRT. This measure, which is referred to as the probability of correct identification, is computed as a function of signal-to-noise ratio (SNR) using the theoretical scattering data from several thin-wire targets. These results are compared to the direct simulation results presented in [1] to demonstrate the accuracy of the analysis.

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