Acoustics

∗Signatures are on file in the Graduate School. This dissertation derives a novel signal processing framework that employs pas-sive sonar to estimate the location of an acoustic source. The approach relies on modeling acoustic propagation, and is designed to estimate the location of a moving source radiating a low frequency tonal signal in a shallow water undersea environment. As the source moves through the ocean, spatial variability in the acoustic field resulting from multi-path propagation is mapped into temporal am-plitude modulation of the received signal. The received signal is measured using a single hydrophone on the sea floor. The recorded amplitude modulation contains information about source location that is encoded by propagation effects. Unfortunately, accurate prediction of the received signal amplitude modulation is complicated by significant uncertainty regarding values of ocean environmental parameters that acoustic propagation models are sensitive to. To increase ro-bustness against the resulting data-model mismatch, the localization framewor