English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A robust adaptive beamforming method is proposed in this paper for uniform linear arrays with respect to sensor gain and phase uncertainties. The sensor gain and phase parameters are obtained by solving a series of linear equations that describe the specific structure of the array covariance matrix for a uniform linear array. Partly calibrated parameter constraints are required due to the rank defect of the coefficient matrix. The necessary condition to enable the partly calibrated sensors to estimate all the unknown gain and phase parameters is also deduced. Sensor noise power, and hence, interference-plus-noise covariance matrix (INCM) can then be calculated with the sensor gain and phase information. The robust adaptive beamformer is finally formed using the reconstructed INCM. In comparison with other reconstruction-based beamformers, the proposed method achieves satisfactory performance when sensor gain and phase uncertainties dominate the steering vector mismatch. The effectiveness of the proposed method is also confirmed by experimental results.

Robust Adaptive Beamforming for Uniform Linear Arrays With Sensor Gain and Phase Uncertainties