Improved bearing estimation in ocean using wavelet denoising

Abstract

Passive localisation and bearing estimation of underwater acoustic sources is a problem of great interest in the area of ocean acoustics. Bearing estimation techniques often perform poorly due to the low signal-to-noise ratio (SNR) at the sensor array. This paper proposes signal enhancement by wavelet denoising to improve the performance of the bearing estimation techniques. Methods have beendeveloped in the recent past to effectively perform wavelet denoising in the multisensor scenario (wavelet array denoising). Following one such approach, the acoustic signal received at the array is spatially decorrelated and then denoised. The denoised and recorrelated signal is then used for bearing estimation employing known bearing estimation techniques (MUSIC and Subspace Intersection). It is shown that wavelet array denoising improves the performance of the bearing estimators significantly. Also the case of perturbed arrays is considered as a special case for application of wavelet array denoising. Simulation results show that the denoising estimator has lower mean square error and higher resolution.