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Computationally efficient ESPRIT algorithm for direction-of-arrival estimation based on Nystrom method
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DOI：10.1016/j.sigpro.2013.05.007.png)
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A low-complexity ESPRIT algorithm for direction-of-arrival (DOA) estimation is devised in this work. Unlike the conventional subspace based methods, the proposed scheme only needs to calculate two sub-matrices of the sample covariance matrix, that is, R-11 is an element of C-KxK and R-21 is an element of C(M-K)xK, avoiding its complete computation. Here, M is the number of sensors of the array, K satisfies P <= K <= min(M,N) with P being the number of source signals and N being the number of snapshots. Meanwhile, a Nystrom-based approach is utilized to correctly compute the signal subspace which only requires O(MK2) flops. Thus, the proposed method has the advantage of computational attractiveness, particularly when K << M. Furthermore, we derive the asymptotic variances of the estimated DOAs. Numerical results are included to demonstrate the effectiveness of the developed DOA estimator. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Direction-of-arrival
Signal subspace
Eigenvalue decomposition
ESPRIT
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