A high resolution direction finding technique for underwater acoustic signal

Abstract

Target estimation in oceanic platform has gained observable engrossment in military and civilized occasions. In this article, the performance of DOA estimation technique based on subspace and the non-subspace analysis have explored. The Subspace analysis of simple resolution and high resolution algorithms, comparisons and the performance of different parameters have discussed. The analysis is based on uniform linear spaced array elements and the estimation depends on the pseudo random spectra function. Customary MUSIC algorithm decomposes the signal covariance matrix into Eigen decomposition and makes the signal subspace matrix orthogonal to the noise subspace, which minimizes the effect of the noise. But, when the signal intervals are very narrow, the existing algorithm cannot separate the correlated sources as SNR reduced to some extent. An advanced algorithm works on factorization of array signal covariance matrix to get Eigen vector and its values. A simulation outcome displays that, projected method gives greater performance compare to the available algorithm. This paper discussed the underwater properties to analyze the performance in noisy surrounding for the new modified MUSIC algorithm.