Two-Dimensional DOA Estimation by Cross-Correlation Submatrix

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Executive Summary

In this paper, the authors present a novel scheme to improve the Two-Dimensional (2-D) Direction-Of-Arrival (DOA) estimation performance for narrowband signals impinging on two orthogonal Uniform Linear Arrays (ULAs). The proposed scheme exploits the cross-correlation sub-matrix information between sub-array data to construct a stacking matrix and derive an expanded signal subspace representation through the Singular Value Decomposition (SVD). This method enables the alleviation of the effects of additive noise. In particular, 2-D DOA estimation can be achieved by computing two rotation matrices with the same set of eigenvectors obtained by partitioning the expanded signal subspace. The pair matching procedure for elevation and azimuth angles is implemented by permutation test.

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