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2D BEAMFORMING ON SPARSE ARRAYS WITH SPARSE BAYESIAN LEARNINGAuthors: Santosh Nannuru,Peter Gerstof Conference: 2019 IEEE International Conference on Acoustics, Speech and Signal Processing Location Brighton, UK. Date: 2019-05-12 Report no: IIIT/TR/2019/24 AbstractSparse 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 beamforming and MUSIC as seen from simulations. Full paper: pdf Centre for Communications |
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