Performance analysis of a GLRT automated target discrimination scheme

Abstract

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.

Performance Analysis of Radar Target Recognition Using Natural Frequency: Frequency Domain Approach

“…The performance analysis of the natural frequency-based radar target recognition in the frequency domain is considered in this paper. The difference between this paper and the previous paper [64] is as follows:…”

“…The authors presented a numerical scheme for performance analysis of the natural frequency-based target discrimination scheme in the time domain [64]. It is based on the binary hypothesis testing and a numerical evaluation of a probability density function (PDF).…”

“…The late time response of a target can be decomposed into a sum of damped sinusoids oscillating at natural frequencies determined by the geometry of the target [60,61]. The natural frequencies of a radar target are aspect independent features of its transient electromagnetic response, and there have been many studies on the natural frequency-based radar target recognition [62][63][64][67][68][69][70].…”

“…The reflected signal of the radar target can be simulated using scattering analysis of the radar target [36][37][38][39][40][41][42][43][44][45][46][47][48][49]. In addition to radar detection and tracking, there have been mamy studies on radar target recognition [3,7,[50][51][52][53][54][55][56][57][58][59][61][62][63][64][65][66][67][68][69][70]. The expressions of recognition, classification and identification have been used interchangeably.…”

“…Radar target recognition is achieved using radar signatures, like natural frequencies of the radar target [60][61][62][63][64][67][68][69][70] high resolution range (HRR) profiles [52,[57][58][59]71] of the radar target and microwave image of the radar target [1-4, 14, 24, 28, 34, 50, 53, 72-83]. Inverse synthetic aperture radar (ISAR) images [3,21,34,[78][79][80][81][82][83] has been one of the most popular microwave imaging techniques for radar target recognition.…”