Abstract : The reported work began as an effort to understand the fundamental differences between target identification techniques based on one-dimensional high range resolution radar and two-dimensional range-Doppler-imaging radar. The work evolved into a more general statistical methodology using target templates to compute the entries in probability (or confusion) matrices, typically used to characterize combat identification (CID) systems. Starting with a set of complex-valued vector target templates, we present a systematic framework for generating and comparing a set of scalar test statistics and estimating their probability of occurrence. These probabilities form the entries of the confusion matrix. We discuss the impact of random noise on the CID process and present the results of applying the template/confusion matrix methodology to a few simple target representations. Specific attention is given to examining the relative issues associated with coherent and noncoherent target identification. For both coherent and noncoherent cases, approximate methods are developed to permit efficient computation of the confusion matrix entries, and the conditions for which these approximations are valid are discussed. Finally, we discuss several real-world, practical issues associated with the template-based methodology and the CID process.
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