ROBUST MATCHED-FIELD LOCALIZATION IN UNCERTAIN OCEAN ENVIRONMENTS

Matched-field source localization methods can be sensitive to environm ental parameter mismatch. A statistically optimal approach to source l ocalization in the presence of environmental uncertainty is the maximu m a posteriori probability (MAP) estimator. Unfortunately, practical i mplementation of the MAP estimator results in a computationally intens ive processor. In this paper, a localization technique is presented th at is a computationally efficient approximation to the MAP estimator. A two-step search procedure is used to estimate source position. The f irst step utilizes an approximation to the MAP estimator which allows much of the computation to be computed efficiently off-line. This step also includes a computationally efficient range-depth smoothing which provides robustness to grid density. In step two, ambiguities arising from step one are resolved using a fine-grid search procedure over th e source location parameters. Simulations using the NRL Workshop bench mark environment, which has seven uncertain environmental parameters, show the performance of the technique to be comparable to that of the MAP estimator while requiring only a fraction of the computations. (C) 1998 Acoustical Society of America.