UC San Diego

Acoustic propagation in shallow water environments is dominated by interactions with the air/water and water/ sediment interfaces, leading to complicated spatio- temporal behavior of the acoustic field. This complexity has proven challenging to the development of shallow ocean acoustic detection, communication, and tomographic applications. One approach to shallow ocean acoustics has been to combine the physics of waveguides with thorough measurement and characterization of the propagation environment to generate accurate acoustic models. However, the costs of characterizing the environment often prove prohibitive. This dissertation develops self-adaptive methods for use in shallow ocean acoustic applications that require no a-priori knowledge of the environment. In contrast to past trends that viewed the complexity of the shallow ocean as a burden, these self-adaptive techniques capitalize on the diversity of the propagation medium. Methods are developed for using vertical geometry acoustic transducer arrays to extract information from the sampled acoustic fields in a range-independent environment. In one scenario, the acoustic response sampled between a pair of arrays is iterated to generate an estimate for the response at longer ranges. In another scenario, a single array is used to extract the modes of acoustic propagation in a range-independent waveguide using a single, partial water column spanning vertical array of acoustic transducers. The mode extraction method is applied to both an ensemble of stationary broadband sources as well as a moving narrowband source subject to arbitrary accelerations. These methods are combined with existing time-reversal techniques to produce a high resolution acoustic focus at an arbitrary location in the shallow ocean waveguide. Simulation, laboratory and at sea experiments support the theory. Though acoustic imaging applications are emphasized in this work, these methods may prove useful for both communications and tomography applications as well