Probability of Resolution of MUSIC and g-MUSIC: An Asymptotic Approach
| Autor: | Schenck D., Mestre X., Pesavento M. |
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| Rok vydání: | 2022 |
| Předmět: |
Eigenvalues and eigenfunctions
Stochastic systems Signal resolution Performances analysis Iterative methods Covariance matrices Cost-function Covariance matrix Direction of arrival Eigenvalue and eigenfunctions Behavioral science Direction of arrival estimation Signal classification Probability of resolution Cost functions Behavioral research Random variables Central Limit Theorem G-multiple signal classification Multiple signal classification |
| Zdroj: | IEEE TRANSACTIONS ON SIGNAL PROCESSING r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) instname |
| ISSN: | 1941-0476 |
| Popis: | In this article, the outlier production mechanism of the conventional Multiple Signal Classification (MUSIC) and the g-MUSIC Direction-of-Arrival (DoA) estimation technique is investigated using tools from Random Matrix Theory (RMT). A general Central Limit Theorem (CLT) is derived that allows to analyze the asymptotic stochastic behavior of eigenvector-based cost functions in the asymptotic regime where the number of snapshots and the number of antennas increase without bound at the same rate. Furthermore, this CLT is used to provide an accurate prediction of the resolution capabilities of the MUSIC and the g-MUSIC DoA estimation method. The finite dimensional distribution of the MUSIC and the g-MUSIC cost function is shown to be asymptotically jointly Gaussian distributed in this asymptotic regime. IEEE |
| Databáze: | OpenAIRE |
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