NDLI: Fast LASSO based DOA tracking

Content Provider	IEEE Xplore Digital Library
Author	Panahi, A. Viberg, M.
Copyright Year	2011
Description	Author affiliation: Signal Processing Group, Departement of Signals and Systems, Chalmers University of Technology, 412 96 Gothenburg, Sweden (Panahi, A.; Viberg, M.)
Abstract	In this paper, we propose a sequential, fast DOA tracking technique using the measurements of a uniform linear sensor array in the far field of a set of narrow band sources. Our approach is based on sparse approximation technique LASSO (Least Absolute Shrincage and Selection Operator), which has recently gained considerable interest for DOA and other estimation problems. Considering the LASSO optimization as a Bayesian estimation, we first define a class of prior distributions suitable for the sparse representation of the model and discuss its relation to the priors over DOAs and waveforms. Inspired by the Kalman filtering method, we introduce a nonlinear sequential filter on this family of distributions. We derive the filter for a simple random walk motion model of the DOAs. The method consists of consecutive implementation of weighted LASSO optimizations using each new measurement and updating the LASSO weights for the next step.
Starting Page	397
Ending Page	400
File Size	274230
Page Count	4
File Format	PDF
ISBN	9781457721045
e-ISBN	9781457721052
DOI	10.1109/CAMSAP.2011.6136036
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laplace equations Bayesian methods Estimation Vectors Approximation methods Arrays Direction of arrival estimation
Content Type	Text
Resource Type	Article

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