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Content Provider | IET Digital Library |
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Author | Huang, Junsheng Su, Hongtao Yang, Yang |
Abstract | 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. |
Starting Page | 7683 |
Ending Page | 7686 |
Page Count | 4 |
Volume Number | 2019 |
e-ISSN | 20513305 |
Issue Number | Issue 21, Nov (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/21 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0739 |
Journal | The Journal of Engineering |
Publisher | The Institution of Engineering and Technology |
Publisher Date | 2019-08-13 |
Access Restriction | Open |
Rights License | Creative Commons Attribution-Non Commercial-No Derivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/) |
Subject Keyword | Algebra Array Signal Processing Covariance Matrices Desired Signal Cancellation Phenomenon Desired Signal Component Desired Signal Steering Vector Estimation Desired Signal Steering Vector Mismatch Digital Signal Processing Eigen Values And Eigen Function Electromagnetic Compatibility Interference Interference-plus-noise Covariance Matrix Reconstruction Linear Algebra Numerical Analysis Optimisation Technique Presumed Desired Signal Steering Vector Robust Adaptive Beamforming Method Sample Covariance Matrix Signal Processing And Detection Signal Processing Theory |
Content Type | Text |
Resource Type | Article |
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