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In shallow water environments, sound propagation experiences multiple interactions with the surface/bottom interfaces, with hydrodynamic disturbances such as internal waves, and with tides and fronts. It is thus very difficult to make satisfactory predictions of sound propagation in shallow water. Given that many of the ocean characteristics can be modeled as stochastic processes, the statistical measure, spatial coherence, is consequently an important quantity. Spatial coherence provides valuable information for array performance predictions. However, for the case of long-range, low frequency propagation, studies of spatial coherence influenced by various environmental parameters are limited insofar as having the appropriate environmental data with which to model and interpret the results. The comprehensive Asian Seas International Experiment 2001 (ASIAEX01) examined acoustic propagation and scattering in shallow water. Environmental oceanographic data were taken simultaneously with the acoustic data. ASIAEX01 provided a unique data set which enabled separate study of the characteristics of the oceanographic features and their influence on long range sound propagation. In this thesis, the environmental descriptors considered include sediment sound speed and attenuation, background internal waves, episodic non-linear internal waves, and air-sea interface conditions. Using this environmental data, the acoustic data are analyzed to show the characteristics of spatial coherence in a shallow water waveguide. It is shown that spatial coherence can be used as an inversion parameter to extract geoacoustic information for the seabed. Environmental phenomena including internal waves and wind-generated surface waves are also studied. The spatial and temporal variations in the sound field induced by them are presented. In addition, a tank experiment is presented which simulates propagation in a shallow water waveguide over a short range. Based on the data model comparison results, the model proposed here is effective in addressing the major environmental effects on sound propagation in shallow water.

This thesis contributes new algorithms and implementations for particle filter-based target tracking. From an algorithmic perspective, modifications that improve a batch-based acoustic direction-of-arrival (DOA), multi-target, particle filter tracker are presented. The main improvements are reduced execution time and increased robustness to target maneuvers. The key feature of the batch-based tracker is an image template-matching approach that handles data association and clutter in measurements. The particle filter tracker is compared to an extended Kalman filter~(EKF) and a Laplacian filter and is shown to perform better for maneuvering targets. Using an approach similar to the acoustic tracker, a radar range-only tracker is also developed. This includes developing the state update and observation models, and proving observability for a batch of range measurements. From an implementation perspective, this thesis provides new low-power and real-time implementations for particle filters. First, to achieve a very low-power implementation, two mixed-mode implementation strategies that use analog and digital components are developed. The mixed-mode implementations use analog, multiple-input translinear element (MITE) networks to realize nonlinear functions. The power dissipated in the mixed-mode implementation of a particle filter-based, bearings-only tracker is compared to a digital implementation that uses the CORDIC algorithm to realize the nonlinear functions. The mixed-mode method that uses predominantly analog components is shown to provide a factor of twenty improvement in power savings compared to a digital implementation. Next, real-time implementation strategies for the batch-based acoustic DOA tracker are developed. The characteristics of the digital implementation of the tracker are quantified using digital signal processor (DSP) and field-programmable gate array (FPGA) implementations. The FPGA implementation uses a soft-core or hard-core processor to implement the Newton search in the particle proposal stage. A MITE implementation of the nonlinear DOA update function in the tracker is also presented.