NDLI: Off-Grid Direction of Arrival Estimation Using Sparse Bayesian Inference

Content Provider	IEEE Xplore Digital Library
Author	Zai Yang Lihua Xie Cishen Zhang
Copyright Year	1991
Abstract	Direction of arrival (DOA) estimation is a classical problem in signal processing with many practical applications. Its research has recently been advanced owing to the development of methods based on sparse signal reconstruction. While these methods have shown advantages over conventional ones, there are still difficulties in practical situations where true DOAs are not on the discretized sampling grid. To deal with such an off-grid DOA estimation problem, this paper studies an off-grid model that takes into account effects of the off-grid DOAs and has a smaller modeling error. An iterative algorithm is developed based on the off-grid model from a Bayesian perspective while joint sparsity among different snapshots is exploited by assuming a Laplace prior for signals at all snapshots. The new approach applies to both single snapshot and multi-snapshot cases. Numerical simulations show that the proposed algorithm has improved accuracy in terms of mean squared estimation error. The algorithm can maintain high estimation accuracy even under a very coarse sampling grid.
Sponsorship	IEEE Signal Processing Society
Starting Page	38
Ending Page	43
Page Count	6
File Size	1499108
File Format	PDF
ISSN	1053587X
Volume Number	61
Issue Number	1
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	Direction of arrival estimation Estimation Bayesian methods Signal to noise ratio Noise measurement Sparse matrices sparse signal reconstruction Compressed sensing direction of arrival estimation off-grid model sparse Bayesian inference
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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