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• W2092267181 abstract "In most cases, we estimate the direction-of-arrivals (DOAs) of signals by using subspace methods, which obtains DOA estimation through the eigenvalue decomposition of the sample covariance matrix. But when the signals are correlative, the sample covariance matrix is not full rank, and so the subspace methods are not applicable. Using a uniform linear array (ULA), a new method for DOA estimation is proposed in this paper, which can estimate the DOAs of multiple signals in spatially nonstationary uncorrelated noise environment. The method firstly constructs a new covariance matrix by using forward/backward smoothing technique, and then the matrix is transformed and construct the differential covariance matrix. Simulation results show that the proposed method can reduce the influence of the noise and improve the performance of DOA estimation. In addition, it is also applicable to the correlative signals." @default.
• W2092267181 created "2016-06-24" @default.
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• W2092267181 date "2013-04-01" @default.
• W2092267181 modified "2023-09-26" @default.
• W2092267181 title "DOA Estimation Method Based on Differential Covariance Matrix" @default.
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• W2092267181 doi "https://doi.org/10.4304/jcp.8.4.1078-1082" @default.
• W2092267181 hasPublicationYear "2013" @default.
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