2005•Systems engineering and electronicsRequires access

Robust adaptive beamforming approach

Chen Si-gen

Open publisher page 0 citations

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.

About this research paper

What this paper is about

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.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available 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.

Key concepts: Adaptive beamformer, Beamforming, Robustness (evolution), Minimum-variance unbiased estimator, Computer science, Bayesian probability, Sensitivity (control systems), Algorithm

Related papers

Back to paper searchBrowse research topicsOriginal source
Robust adaptive beamforming approach — Research Paper | ScholarLens