A High Resolution Direction Finding Technique for Underwater Acoustic Signal
Prashil M. Junghare1, Cyril Prasanna Raj P.2, T Srinivas3
1Kavin. R, Department of EEE, Sri Krishna College of Engineering and Technology, Coimbatore (Tamil Nadu), India.
2Elamcheren. S, Department of EEE, Sri Krishna College of Engineering and Technology, Coimbatore (Tamil Nadu), India.
3Dr. S. Sheebarani Gnanamalar, Department of EEE, Sri Krishna College of Engineering and Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 192-198 | Volume-8 Issue-4, April 2019 | Retrieval Number: C5922028319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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.
Keywords: DOA Estimation; Subspace Analysis; Uniform Linear Array (ULA); Signal Covariance Matrix; MUSIC Algorithm
Scope of the Article: Algorithm Engineering