Abstract
Detection, classification, and localization of underwater objects is a primary function of active sonar systems. Detection involves making a decision on whether or not an object of interest is present. Once a positive detection has been made, further information may be needed to classify the object as one among a set of possible objects of interest. Previous efforts have been directed at designing transmit sonar waveforms to maximize detection performance. In this work, we extend the optimal sonar design approach to enhance classification after detection. In particular, we present an optimal signal design approach that is aimed at maximizing the probability of correctly classifying the true target from among a set of assumed candidates. The approach is evaluated theoretically and via simulations, by which it is shown that waveform design can yield improvements in classification performance. [Work supported by ONR.]
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