Robust adaptive beamforming method based on desired signal steering vector estimation and interference-Plus-noise covariance matrix reconstruction
| Autor: | Hongtao Su, Junsheng Huang, Yang Yang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
MathematicsofComputing_NUMERICALANALYSIS Energy Engineering and Power Technology 02 engineering and technology Signal desired signal component interference-plus-noise covariance matrix reconstruction Interference (communication) desired signal steering vector mismatch Convergence (routing) 0202 electrical engineering electronic engineering information engineering Sine array signal processing Eigenvalues and eigenvectors presumed desired signal steering vector Covariance matrix Noise (signal processing) 020208 electrical & electronic engineering General Engineering covariance matrices 020206 networking & telecommunications robust adaptive beamforming method desired signal steering vector estimation sample covariance matrix lcsh:TA1-2040 desired signal cancellation phenomenon eigenvalues and eigenfunctions lcsh:Engineering (General). Civil engineering (General) Algorithm Adaptive beamformer Software |
| Zdroj: | The Journal of Engineering (2019) |
| DOI: | 10.1049/joe.2019.0739 |
| Popis: | Here, the authors propose a robust adaptive beamforming method based on desired signal steering vector estimation and interference-plus-noise covariance matrix reconstruction, so as to attenuate the influences of the desired signal steering vector mismatch and the limited training snapshots on the performance of adaptive beamformer. More precisely, the desired signal steering vector is estimated by minimising the sine value of the angle between the presumed desired signal steering vector and the eigenvectors of sample covariance matrix. Besides, the sample covariance matrix is reconstructed by reducing the dispersion extent of the noise eigenvalues and eliminating the desired signal component from the sample covariance matrix. The proposed method can not only accelerate the convergence speed of adaptive beamforming algorithm, but also avoid the desired signal cancellation phenomenon when the desired signal is present in the training snapshots. Simulation results demonstrate the superiority of the proposed method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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