New method of DOA estimation for coherent sources under unknown noise field
Shujing Su, Zenggang Wang, Jinglong Yan
Abstract
Shujing Su, Zenggang Wang, Jinglong Yan
Abstract
The major shortcomings of the MUSIC algorithm for direction-of arrival (DOA) are that it performs poorly when the sources are highly and when the noise is unknown. A method was proposed to estimate DOA for coherent, noncoherent, and mixed narrowband signals under an unknown spatially noise environment, in this method, the forward-backward spatial smoothing algorithm was employed to decorrelate highly correlated sources and increase data amount, and a covariance matrix difference between the forward-backward spatial smoothing for covariance matrix of the received data and its transform matrix was introduced to eliminate noise components from the array structure, then, the MUSIC spectral was constructed by eigenvalue decomposition the difference to estimate DOA of signal sources. The numerical result verified that the method is effective.
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The major shortcomings of the MUSIC algorithm for direction-of arrival (DOA) are that it performs poorly when the sources are highly and when the noise is unknown. A method was proposed to estimate DOA for coherent, noncoherent, and mixed narrowband signals under an unknown spatially noise environment, in this method, the forward-backward spatial smoothing algorithm was employed to decorrelate highly correlated sources and increase data amount, and a covariance matrix difference between the forward-backward spatial smoothing for covariance matrix of the received data and its transform matrix was introduced to eliminate noise components from the array structure, then, the MUSIC spectral was constructed by eigenvalue decomposition the difference to estimate DOA of signal sources. The numerical result verified that the method is effective.
Key concepts: Smoothing, Narrowband, Covariance matrix, Algorithm, Noise (video), Direction of arrival, Eigendecomposition of a matrix, Computer science