Acoustic prediction in shallow water from sparse data

Abstract

Consider the problem of estimating acoustic propagation over extended ranges in shallow water. Such predictions would be useful in deploying assets, locating sources, or oceanographic monitoring. Given adequate environmental information, standard numerical techniques could be applied. For a highly variable site, however, the medium would rarely be known with sufficient resolution to make accurate calculations. Direct acoustic measurements suffer from a similar lack of resolution; isolated point-to-point measurements cannot fully characterize acoustic propagation over a large region. In this talk, a hybrid numerical/experimental technique is examined. In the proposed approach, sparse environmental measurements are supplemented by making a limited number of acoustic measurements. By appropriately combining the two data sets and extrapolating, acoustic propagation over an extended region can be accurately predicted. The method is tested using archival sound speed and bathymetric data for a strongly range-dependent site. The relative effects on the propagating acoustic wave front of variations in bathymetry, imperfect knowledge of the sediment, and variability in the water column are quantified. [Work supported by ONR and NRL.]