Source localization in an acoustic waveguide with uncertain sound speed

Matched-field source localization methods attempt to estimate the range and depth of a source in an acoustic waveguide. These methods give good results when the waveguide parameters are known precisely; however, matched-field methods have been shown to be very sensitive to model mismatch resulting from errors in the assumed environmental parameters. In this paper, we describe an approach which minimizes model mismatch by estimating the environmental parameters and source location together. We propose an efficient way to initialize the maximum-likelihood search by projecting the received data onto subspaces corresponding to regions in parameter space