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Journal Article
Asymptotic Performance Analysis of the MUSIC Algorithm for Direction-of-Arrival Estimation
- Authors
- So-Hee Jeong, Byung-kwon Son, Joon-Ho Lee
- Issue Date
- 2020-03
- Citation
- Applied Sciences, v.10, no.6, pp.1-25
- ISSN
- 2076-3417
- Publisher
- MDPI
- Language
- English
- Type
- Journal Article
- Project Code
- 20ZD1100, 대경권 지역산업 기반 ICT 융합기술 고도화 지원사업, Moon Ki Young
- Abstract
- We consider the performance analysis of the multiple signal classification (MUSIC) algorithm for multiple incident signals when the uniform linear array (ULA) is adopted for estimation of the azimuth of each incident signal. We derive closed-form expression of the estimation error for each incident signal. After some approximations, we derive closed-form expression of the mean square error (MSE) for each incident signal. In the MUSIC algorithm, the eigenvectors of covariance matrix are used for calculation of the MUSIC spectrum. Our derivation is based on how the eigenvectors of the sample covariance matrix are related to those of the true covariance matrix. The main contribution of this paper is the reduction in computational complexity for the performance analysis of the MUSIC algorithm in comparison with the traditional Monte-Carlo simulation-based performance analysis. The validity of the derived expressions is shown using the numerical results. Future work includes an extension to performance analysis of the MUSIC algorithm for simultaneous estimation of the azimuth and the elevation.
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
