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Structured Autocorrelation Matrix Estimation for Coprime Arrays

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Document pages: 11 pages

Abstract: A coprime array receiver processes a collection of received-signal snapshotsto estimate the autocorrelation matrix of a larger (virtual) uniform lineararray, known as coarray. By the received-signal model, this matrix has to be(i) Positive-Definite, (ii) Hermitian, (iii) Toeplitz, and (iv) itsnoise-subspace eigenvalues have to be equal. Existing coarray autocorrelationmatrix estimates satisfy a subset of the above conditions. In this work, wepropose an optimization framework which offers a novel estimate satisfying allfour conditions. Numerical studies illustrate that the proposed estimateoutperforms standard counterparts, both in autocorrelation matrix estimationerror and Direction-of-Arrival estimation.

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