Performance analysis of an automated E-pulse target discrimination scheme

An automated E-pulse scheme for target discrimination was initially presented by Ilavarasan et al. (1993) without an analytic performance evaluation. Assuming that target responses are contaminated with white Gaussian noise, an automated E-pulse scheme is rigorously analyzed to yield a reliable measure of performance. The discrimination performance of this automated E-pulse scheme is determined quantitatively through the use of energy discrimination numbers (EDNs). Statistics of the EDNs are evaluated analytically to derive the probability of correct identification. The probability of identification as a function of signal-to-noise ratio (SNR) is evaluated using the theoretical scattering data for all potential targets to predict the performance of the automated E-pulse scheme. These theoretical results are corroborated by direct simulation of the discrimination scheme. In addition, the probability density functions of the EDNs are presented providing new physical insights into E-pulse performance as a function of target geometries and SNR