Multisnapshot Sparse Bayesian Learning for DOA

Peter Gerstoft, Christoph F. Mecklenbrauker, Angeliki Xenaki, Santosh Nannuru

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

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.
Original languageEnglish
JournalIEEE Signal Processing Letters
Volume23
Issue number10
Pages (from-to)1469-1473
Number of pages5
ISSN1070-9908
DOIs
Publication statusPublished - 2016

Keywords

  • Array processing
  • compressive beamforming
  • directions of arrival (DOA) estimation
  • relevance vector machine
  • sparse reconstruction
  • Beamforming
  • Gaussian distribution
  • Complex Gaussian
  • Conventional beamforming
  • Posterior distributions
  • Relevance Vector Machine
  • Sparse Bayesian learning
  • Sparse Bayesian learning (SBL)
  • Sparse reconstruction
  • Zero-mean complex
  • Direction of arrival
  • Direction-of-arrival estimation
  • Covariance matrices
  • Arrays
  • Bayes methods
  • Estimation
  • Array signal processing
  • Signal processing algorithms
  • Arrayprocessing
  • compressivebeamforming
  • Signal processing and detection
  • Sensing devices and transducers
  • Other topics in statistics
  • Digital signal processing
  • Knowledge engineering techniques
  • direction-of-arrival estimation
  • learning (artificial intelligence)
  • sensor arrays
  • sparse Bayesian learning
  • directions of arrival
  • plane waves
  • multisnapshot sensor array data
  • SBL
  • source amplitudes
  • independent zero-mean complex Gaussian distribution
  • hyperparameters
  • source powers
  • complex Gaussian likelihood
  • DOA estimation

Fingerprint

Dive into the research topics of 'Multisnapshot Sparse Bayesian Learning for DOA'. Together they form a unique fingerprint.

Cite this