Autoregressive Power Spectrum-Based Covariance Matrix Reconstruction for Robust Adaptive Beamforming
In this paper, a new robust adaptive beamforming method based on the autoregressive (AR) power spectrum is proposed. To improve the robustness of the Capon spectrum, the AR model is applied to realize the desired signal power and interference power estimations, which are used to reconstruct the cova...
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| Veröffentlicht in: | Circuits, systems, and signal processing systems, and signal processing, 2024-02, Vol.43 (2), p.1157-1174 |
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| container_title | Circuits, systems, and signal processing |
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| creator | Yang, Huichao Dong, Linjie |
| description | In this paper, a new robust adaptive beamforming method based on the autoregressive (AR) power spectrum is proposed. To improve the robustness of the Capon spectrum, the AR model is applied to realize the desired signal power and interference power estimations, which are used to reconstruct the covariance matrix. Besides, the eigenvalue decomposition is used to remove the redundancy of the reconstructed interference-plus-noise covariance matrix, where the number of interferences is confirmed by the maximum ratio index of the adjacent eigenvalues. Numerical simulations highlight that the proposed method is more robust against some common errors compared with several beamformers. |
| doi_str_mv | 10.1007/s00034-023-02508-x |
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| ispartof | Circuits, systems, and signal processing, 2024-02, Vol.43 (2), p.1157-1174 |
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| source | SpringerNature Journals |
| subjects | Arrays Autoregressive processes Beamforming Circuits and Systems Convex analysis Covariance matrix Decomposition Eigenvalues Electrical Engineering Electronics and Microelectronics Engineering Instrumentation Interference Mathematical models Methods Optimization Redundancy Robustness (mathematics) Sensors Signal processing Signal,Image and Speech Processing |
| title | Autoregressive Power Spectrum-Based Covariance Matrix Reconstruction for Robust Adaptive Beamforming |
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