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학술지 Asymptotic Performance Analysis of the MUSIC Algorithm for Direction-of-Arrival Estimation
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저자
정소희, 손병권, 이준호
발행일
202003
출처
Applied Sciences, v.10 no.6, pp.1-25
ISSN
2076-3417
출판사
MDPI
DOI
https://dx.doi.org/10.3390/app10062063
협약과제
20ZD1100, 대경권 지역산업 기반 ICT 융합기술 고도화 지원사업, 문기영
초록
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.
키워드
Analytic performance analysis, Multiple signal classification (MUSIC), Root mean square (RMS), Taylor series, Uniform linear array (ULA)
KSP 제안 키워드
Closed-form expressions, Computational complexity, Direction of arrival(DoA), Direction of arrival estimation, Monte-Carlo simulation(MCS), Multiple signal classification (MUSIC) algorithm, Numerical results, Performance analysis, Root mean square(RMS), Sample covariance matrix, Simultaneous estimation
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