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Acoustic waves in water are used to detect or locate targets, measure environmental or target parameters and transmit signals. Although detection and localization of an underwater source (target) have been the primary need in military applications, they have been found many commercial applications as well. In this work, we consider the problem of detection and localization of acoustic sources in the presence of non Gaussian noise. Although assumption of Gaussian distribution for ambient noise provides simplicity and tractability, it is not a valid assumption when a large number of impulses appear in the background noise, such as warm water shallow oceans. Two main sources that contribute to the non Gaussianity of ambient noise are biological noise produced by some marine organisms such as snapping shrimp, and navigation noise. When noise is non Gaussian, the performance of linear signal processing techniques that have been derived based on the assumption of Gaussian noise characteristics degrade. In these cases, nonlinear processing techniques are more effective. We investigate a number of nonlinear methods for detecting and localizing acoustic sources in the presence of highly non Gaussian noise. We present a robust and easily implementable detector based on nonlinear wavelet denoising (NWD) for detection of signals. A class of nonlinear median based transforms has been chosen for denoising since the conventional denoising techniques based on linear wavelet transforms are suitable only for denoising signals in Gaussian noise. The proposed NWD detector offers the following advantages for signal detection in strongly non Gaussian noise: (1) significantly better performance than the matched filter, (2) greater robustness than the optimal detector, (3) moderate computational complexity. Further, we develop a computationally simple algorithm known as SAGE USL, for 3 dimensional (3 D) localization of multiple acoustic sources in shallow ocean. In this algorithm, a hybrid array of sensors composed of a vertical and a horizontal linear array is used. In the SAGE USL algorithm, after a rough estimate of different unknown parameters, a novel SAGE

Nonlinear techniques for source detection and localization in shallow ocean with non-Gaussian noise