Robust adaptive beamforming approach
Chen Si-gen
Abstract
Chen Si-gen
Abstract
Based on the principle of linearly constrained minimum variance (LCMV) adaptive beamforming, an adaptive beamforming method by using Bayesian posterior probability weighted sum is proposed in terms of the Bayesian estimation theory. The method is developed to improve robustness to pointing error and overcome the shortcoming of LCMV beamforming's sensitivity to pointing error. The results of simulation indicate that the performance of the proposed beamforming method is robust to the pointing error.
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Based on the principle of linearly constrained minimum variance (LCMV) adaptive beamforming, an adaptive beamforming method by using Bayesian posterior probability weighted sum is proposed in terms of the Bayesian estimation theory. The method is developed to improve robustness to pointing error and overcome the shortcoming of LCMV beamforming's sensitivity to pointing error. The results of simulation indicate that the performance of the proposed beamforming method is robust to the pointing error.
Key concepts: Adaptive beamformer, Beamforming, Robustness (evolution), Minimum-variance unbiased estimator, Computer science, Bayesian probability, Sensitivity (control systems), Algorithm