NDLI: Direction-of-arrival estimation of incoherently distributed sources using Bayesian compressive sensing

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Direction-of-arrival estimation of incoherently distributed sources using Bayesian compressive sensing

Content Provider	IET Digital Library
Author	Yang, Xuemin Ko, Chi Chung Zheng, Zhi
Abstract	Much attention has recently been paid to incoherently distributed sources (IDSs) in this field of direction-of-arrival (DOA) estimation of distributed sources. This study introduces the sparse reconstruction theory to DOA estimation of IDSs and proposes two DOA estimation methods of IDSs based on different sparse representations. First, the DOA estimation problem of IDSs is translated into a sparse reconstruction problem by building two parametric sparse representation models (on-grid and off-grid), which indicate the fact that the central DOAs of IDSs may be not on the discretised sampling grid. Then, based on the two different models, the corresponding sparse reconstruction problem is solved using the Bayesian compressive sensing method. Accordingly, the central DOA estimation of IDSs is also obtained. Compared with the existing methods, the authors’ approach can provide a better performance under the condition of low signal-to-noise ratio, limited number of snapshots and closely spaced sources. Simulation results demonstrate the effectiveness of the proposed methods.
Starting Page	1057
Ending Page	1064
Page Count	8
ISSN	17518784
Volume Number	10
e-ISSN	17518792
Issue Number	Issue 6, Jul (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/10/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2015.0336
Journal	IET Radar, Sonar & Navigation
Publisher Date	2016-07-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bayes Method Bayesian Compressive Sensing Method Compressed Sensing Direction of Arrival Estimation DOA Estimation Problem IDS Incoherently Distributed Source Low Signal-to-noise Ratio Off-grid Two Parametric Sparse Representation Model On-grid Two Parametric Sparse Representation Model Signal Processing And Detection Signal Processing Theory Signal Representation Sparse Reconstruction Theory Statistics
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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