2D Beamforming on Sparse Arrays with Sparse Bayesian Learning

Santosh Nannuru; Peter Gerstoft

ICASSP 2019accepted0 citations

2D Beamforming on Sparse Arrays with Sparse Bayesian Learning

Abstract

Sparse arrays such as co-prime and nested arrays can identify more sources than the number of sensors. This is because their difference co-arrays contain a uniformly spaced virtual array with more elements than the number of sensors in the array. In this paper we demonstrate this using two dimensional co-prime and nested sparse arrays combined with sparse Bayesian learning (SBL) for 2D beamforming in azimuth and elevation. SBL can directly process the sparse array data and significantly outperform conventional beam-forming and MUSIC as seen from simulations.

BibTeX

@inproceedings{icassp2019_2dbeamformingons,
  title = {2D Beamforming on Sparse Arrays with Sparse Bayesian Learning},
  author = {Santosh Nannuru and Peter Gerstoft},
  booktitle = {ICASSP 2019},
  year = {2019}
}