A Low Complexity Subspace-Based DOA Estimation Algorithm with Uniform Linear Array Correlation Matrix Subsampling
- Authors
- Yoo, Do-Sik
- Issue Date
- 2015
- Publisher
- HINDAWI PUBLISHING CORP
- Citation
- INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION, v.2015
- Journal Title
- INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION
- Volume
- 2015
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/10969
- DOI
- 10.1155/2015/323545
- ISSN
- 1687-5869
- Abstract
- We propose a low complexity subspace-based direction-of-arrival (DOA) estimation algorithm employing a direct signal space construction method (DSPCM) by subsampling the autocorrelation matrix of a uniform linear array (ULA). Three major contributions of this paper are as follows. First of all, we introduce the method of autocorrelation matrix subsampling which enables us to employ a low complexity algorithm based on a ULA without computationally complex eigenvalue decomposition or singularvalue decomposition. Secondly, we introduce a signal vector separation method to improve the distinguishability among signal vectors, which can greatly improve the performance, particularly, in low signal-to-noise ratio (SNR) regime. Thirdly, we provide a root finding (RF) method in addition to a spectral search (SS) method as the angle finding scheme. Through simulations, we illustrate that the performance of the proposed scheme is reasonably close to computationally much more expensive MUSIC-(MUltiple SIgnal Classification-) based algorithms. Finally, we illustrate that the computational complexity of the proposed scheme is reduced, in comparison with those of MUSIC-based schemes, by a factor of O(N-2/K), where K is the number of sources and.. is the number of antenna elements.
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Collections - College of Engineering > School of Electronic & Electrical Engineering > 1. Journal Articles
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