Sparse-reconstruction-based high resolution beamforming and its application to multi-beam systems

In this paper, we present a high resolution beam-forming (BF) method for multi-beam systems based on sparse reconstruction algorithms. The beamforming problem is represented as solving an underdetermined linear equation. By enforcing the spatial sparsity of echoes for each snapshot, the signal strength on a specfied direction of arrival (DOA) grid is solved using sparse reconstruction algorithms. Furthermore, a local refinement to conventional beamforming and using samples from the beam domain are proposed to increase grid accuracy and signal-to-noise ratio (SNR) of the measurements. Both simulated data and experimental data are processed to demonstrate the effectiveness of our proposed method applied to multi-beam systems. We observe that our method can achieve sharpened bottom echo curve and suppress grating lobes inherent in the system.