Abstract:
Active detection and localization of a target using a horizontal array is implemented via optimum physics-based signal processing. This approach provides a robust method of detection and localization by incorporating any a priori knowledge of the physical environment, however uncertain or incomplete. The active return from a target in a dense multipath environment is assumed to be well modeled as the sum of weighted, delayed, and phase-shifted replicas of the active source transmission. These signal model parameters (i.e., the set of weights, delays, and phase shifts) vary as a function of the physical environment. An acoustic propagation model drives the optimum detector by mapping prior descriptions of the physical environment to a stochastic description of the signal model parameters. The optimum processor additionally provides localization estimates in bearing, range, and depth for a horizontal array. Illustrative simulation results will be presented in the form of receiver operator characteristics (ROC). Experimental results are anticipated. [Work supported by Digital System Resources.]