Journal
IEEE SIGNAL PROCESSING LETTERS
Volume 23, Issue 10, Pages 1469-1473Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2016.2598550
Keywords
Array processing; compressive beamforming; directions of arrival (DOA) estimation; relevance vector machine; sparse reconstruction
Categories
Funding
- Office of Naval Research [N00014-1110439]
- Forschungszentrum Telekommunikation Wien Austria
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The directions of arrival (DOA) of plane waves are estimated from multisnapshot sensor array data using sparse Bayesian learning (SBL). The prior for the source amplitudes is assumed independent zero-mean complex Gaussian distributed with hyperparameters, the unknown variances (i.e., the source powers). For a complex Gaussian likelihood with hyperparameter, the unknown noise variance, the corresponding Gaussian posterior distribution is derived. The hyperparameters are automatically selected by maximizing the evidence and promoting sparse DOA estimates. The SBL scheme for DOA estimation is discussed and evaluated competitively against LASSO (l(1)-regularization), conventional beamforming, and MUSIC.
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