Constant-Beamwidth Linearly Constrained Minimum Variance Beamformer
Ariel J. Frank, Assaf Ben-Kish, Israel Cohen · 2022 30th European Signal Processing Conference (EUSIPCO) · 2022
In this paper, we propose a new and flexible method for designing a constant-beamwidth beamformer that maintains directional constraints. We decompose the problem by designing a linearly constrained minimum variance beamformer and a constant-beamwidth beamformer based on the window technique. Subsequently, we utilize Kronecker product beamforming to merge the two elementary beamformers. While a competing method restricts the beamwidth depending on the interelement spacing and number of sensors in the array, the proposed method enables a flexible design of an arbitrary beamwidth. Experimental results demonstrate the improved performance of the proposed approach compared to the competing method. Specifically, the proposed beamformer achieves the desired beamwidth and directional constraints with a significantly higher directivity factor and lower sidelobe levels.