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Robust Adaptive Beamforming Algorithm with a Quadratic Constraint |
Song Xin Wang Jin-kuan Han Ying-hua |
(School of Information Science & Engineering, Northeastern University, Shenyang 110004, China) |
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Abstract The performance of adaptive beamforming algorithms is known to degrade severely in the presence of even slight signal steering vector mismatches. To account for the mismatches, a novel robust adaptive beamforming algorithm is proposed. To improve robustness, the weight vector is optimized to involve minimization of a quadratic function subject to the norm of error between the actual and assumed signal steering vectors and the parameter in the optimal solution can be solved accurately. The proposed algorithm can suffer the least distortion from the directions near the steering angle, reduce the influence of the mismatches, and provide an improved robustness against the mismatches. Moreover, it can suppress the interference signals and make the mean output array SINR consistently close to the optimal one. Simulation results demonstrate its validity and superiority as compared with the conventional algorithms.
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Received: 14 May 2007
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Corresponding Authors:
Song Xin
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