Robust Broadband Beamforming using Bilinear Programming

TL;DR

This paper presents a robust broadband beamforming method that estimates signals under angle uncertainty by solving a bilinear inverse problem, achieving near-optimal performance even with limited angle information.

Contribution

It introduces a novel bilinear programming approach for robust beamforming that handles unknown forward models and improves performance over existing methods.

Findings

State-of-the-art narrowband performance achieved

Effective broadband signal estimation demonstrated

Minimal performance loss with uncertain angle of arrival

Abstract

We introduce a new method for robust beamforming, where the goal is to estimate a signal from array samples when there is uncertainty in the angle of arrival. Our method offers state-of-the-art performance on narrowband signals and is naturally applied to broadband signals. Our beamformer operates by treating the forward model for the array samples as unknown. We show that the "true" forward model lies in the linear span of a small number of fixed linear systems. As a result, we can estimate the forward operator and the signal simultaneously by solving a bilinear inverse problem using least squares. Our numerical experiments show that if the angle of arrival is known to only be within an interval of reasonable size, there is very little loss in estimation performance compared to the case where the angle is known exactly.