NDLI: A new direction-of-arrival estimation method exploiting signal structure information

Content Provider	Springer Nature Link
Author	Lin, Bo Liu, Jiying Xie, Meihua Zhu, Jubo Yan, Fengxia
Copyright Year	2015
Abstract	A new method is proposed to estimate the direction-of-arrival (DOA) based on uniform linear array sampling and named as sparsity and temporal correlation exploiting (SaTC-E). By exploiting the structure information of source signals, including spatial sparsity and temporal correlation of sources, SaTC-E accomplishes DOA estimation with superior performance via block sparse bayesian learning methodology and grid refined strategy. SaTC-E is applicable into time-varying manifold scenario, such as wideband sources, time-varying array, provided that the array manifold matrix is determinable. It has improved performance with some other merits, including superior resolution, requirement for a few snapshots, no knowledge of source number, and applicability to spatially and temporally corrected sources. Real data tests and numerical simulations are carried out to demonstrate the advantages of SaTC-E.
Starting Page	183
Ending Page	205
Page Count	23
File Format	PDF
ISSN	09236082
Journal	Multidimensional Systems and Signal Processing
Volume Number	28
Issue Number	1
e-ISSN	15730824
Language	English
Publisher	Springer US
Publisher Date	2015-07-02
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Direction-of-arrival (DOA) estimation Block sparse bayesian learning (BSBL) Temporal correlation Spatial joint sparsity Grid refined strategy Circuits and Systems Electrical Engineering Signal,Image and Speech Processing Artificial Intelligence (incl. Robotics)
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Signal Processing Information Systems Computer Science Applications Software Hardware and Architecture

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