Abstract
Active, wideband detection and localization of targets in a dense multipath environment is approached via optimal detection and estimation theory in conjunction with a received signal model described by weighted, delayed, and phase-shifted replicas of the transmitted signal. These multipath signal parameters are known to vary with acoustic medium properties including sound-speed profile, bottom composition and topography, and sea surface state. The optimum receiver is a time domain processor based on the statistical properties of the multipath parameters. An acoustic propagation model drives the optimum receiver by mapping acoustic medium parameters to multipath signal parameters through Monte Carlo simulation. The generic sonar model (GSM) software package provides the required simulation environment. Illustrative detection and localization examples are presented in the form of receiver operator characteristics (ROC) and localization ROCs, respectively. Results demonstrate significant improvement in detection and localization over standard matched filtering, even with uncertainty of the physical environment and random effects of boundary scattering.
Published Version
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