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Robust and Computationally Efficient Signal-Dependent Method for Joint DOA and Frequency Estimation

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Abstract

The problem of joint direction of arrival (DOA) and frequency estimation is considered in this paper. A new method is proposed based on the signal-dependent multistage wiener filter (MWF). Compared with the classical subspace-based joint DOA and frequency estimators, the proposed method has two major advantages: (1) it provides a robust performance in the presence of colored noise; (2) it does not involve the estimation of covariance matrix and its eigendecomposition, and thus, yields much lower computational complexity. These advantages can potentially make the proposed method more feasible in practical applications. The conditional Cramér-Rao lower bound (CRB) on the error variance for joint DOA and frequency estimation is also derived. Both numerical and experimental results are used to demonstrate the performance of the proposed method.

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Correspondence to Ting Shu.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Shu, T., Liu, X. Robust and Computationally Efficient Signal-Dependent Method for Joint DOA and Frequency Estimation. EURASIP J. Adv. Signal Process. 2008, 134853 (2008). https://doi.org/10.1155/2008/134853

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Keywords

  • Covariance
  • Information Technology
  • Covariance Matrix
  • Computational Complexity
  • Quantum Information