非均匀噪声稀疏均匀圆阵的二维DOA估计

Abstract

Abstract: Uniform circular arrays (UCAs) are widely used in airborne radar and communication applications. This article addresses the 2-D DOA estimation for sparse UCA in the presence of unknown nonuniform noise. First of all, the beamspace likelihood function for sparse UCA in the nonuniform noise is constructed by means of the modified phase-mode principle. Then, based on an analysis of the beamspace likelihood function of sparse UCA in the nonuniform noise, Burg’s inverse iteration algorithm is modified to estimate the noise covariance matrix of the nonuniform noise on the sparse UCA. Finally, by deriving the gradient and the asymptotic Hessian matrix of the likelihood function in the nonuniform noise, the angle parameters are estimated based on the (Modified Variable Projection, MVP) method. The simulation results show that the proposed method has better performance than sparse UCA root-MUSIC and the traditional maximum-likelihood algorithm. This method can deal with coherent sources as well.

Key words: uniform circular array (UCA), direction of arrival (DOA), nonuniform noise, sensor array processing, maximum likelihood

CLC Number:

PAN Jie, ZHOU Jianjiang, WANG Fei. 2-D DOA Estimation for Sparse Uniform Circular Array in Presence of Unknown Nonuniform Noise[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2011, 32(3): 448-456.

References

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2-D DOA Estimation for Sparse Uniform Circular Array in Presence of Unknown Nonuniform Noise

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