NDLI: Sequential Bayesian Sparse Signal Reconstruction Using Array Data

Content Provider	IEEE Xplore Digital Library
Author	Mecklenbrauker, C.F. Gerstoft, P. Panahi, A. Viberg, M.
Copyright Year	1991
Abstract	In this paper, the sequential reconstruction of source waveforms under a sparsity constraint is considered from a Bayesian perspective. Let the wave field, which is observed by a sensor array, be caused by a spatially-sparse set of sources. A spatially weighted Laplace-like prior is assumed for the source field and the corresponding weighted Least Absolute Shrinkage and Selection Operator (LASSO) cost function is derived. After the weighted LASSO solution has been calculated as the maximum a posteriori estimate at time step k, the posterior distribution of the source amplitudes is analytically approximated. The weighting of the Laplace-like prior for time step k+1 is then fitted to the approximated posterior distribution. This results in a sequential update for the LASSO weights. Thus, a sequence of weighted LASSO problems is solved for estimating the temporal evolution of a sparse source field. The method is evaluated numerically using a uniform linear array in simulations and applied to data which were acquired from a towed horizontal array during the long range acoustic communications experiment.
Sponsorship	IEEE Signal Processing Society
Starting Page	6344
Ending Page	6354
Page Count	11
File Size	3352607
File Format	PDF
ISSN	1053587X
Volume Number	61
Issue Number	24
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Arrays Vectors Bayes methods Cost function Estimation Compressed sensing Position measurement weighted LASSO Bayesian estimation sequential estimation sparsity
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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