A novel deflation approach to direction of arrival (DOA) estimation for symmetric uniform linear array is proposed in this letter to cope with the scenario where both uncorrelated sources and coherent sources are pres...
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A novel deflation approach to direction of arrival (DOA) estimation for symmetric uniform linear array is proposed in this letter to cope with the scenario where both uncorrelated sources and coherent sources are presented. The uncorrelated sources are first estimated using conventional subspace methods, and then their effect is eliminated by two deflation methods: one exploits the symmetric configuration of the array, and the other utilizes oblique projection. After deflation, a Toeplitz matrix is constructed for DOA estimation of the remaining coherent sources. The number of sources resolved by our approach can exceed the number of array elements. Simulation results demonstrate the effectiveness and efficiency of our proposed methods.
A novel algorithm is proposed for the direction of-arrival (DOA) estimation of coherently distributed (CD) sources. Based on the symmetric property of the uniformlineararray (ULA) geometry, the DOA can be estimated ...
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ISBN:
(纸本)9781538620625
A novel algorithm is proposed for the direction of-arrival (DOA) estimation of coherently distributed (CD) sources. Based on the symmetric property of the uniformlineararray (ULA) geometry, the DOA can be estimated by a one-dimensional peak search without estimating the distribution parameters, where N independent CD sources can be distinguished with a ULA of 2N + 1 elements. Compared with the existing algorithms, our proposed algorithm achieves higher element utilization rate with lower computational complexity. Numerical simulation results demonstrate our proposed algorithm provides an improved performance over the generalized eigenvalue decomposition (GEVD) algorithm.
In this paper, we investigate the problem of estimating the directions-of-arrival (DOAs) and ranges of multiple narrowband near-field sources in unknown spatially nonuniform noise (spatially inhomogeneous temporary wh...
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In this paper, we investigate the problem of estimating the directions-of-arrival (DOAs) and ranges of multiple narrowband near-field sources in unknown spatially nonuniform noise (spatially inhomogeneous temporary white noise) environment, which is usually encountered in many practical applications of sensor array processing. A new subspace-based localization of near-field sources (SLONS) is proposed by exploiting the advantages of a symmetricuniformlinear sensor array and using Toeplitzation of the array correlations. Firstly three Toeplitz correlation matrices are constructed by using the anti-diagonal elements of the array covariance matrix, where the nonuniform variances of additive noises are reduced to a uniform one, and then the location parameters (i.e., the DOAs and ranges) of near-field sources can be estimated by using the MUSIC-like method, while a new pair-matching scheme is developed to associate the estimated DOAs and ranges. Additionally, an alternating iterative scheme is considered to improve the estimation accuracy of the location parameters by utilizing the oblique projection operator, where the "saturation behavior" caused by finite number of snapshots is overcome effectively. Furthermore, the closed-form stochastic Cramer-Rao lower bound (CRB) is also derived explicitly for the near-field sources in the additive unknown nonuniform noises. Finally, the effectiveness of the proposed method and the theoretical analysis are substantiated through numerical examples.
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