DocumentCode :
36606
Title :
Distributed Compressed Sensing off the Grid
Author :
Zhenqi Lu ; Rendong Ying ; Sumxin Jiang ; Peilin Liu ; Wenxian Yu
Author_Institution :
Dept. of Electr. Eng., Shanghai Jiao Tong Univ., Shanghai, China
Volume :
22
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
105
Lastpage :
109
Abstract :
This letter investigates the joint recovery of a frequency-sparse signal ensemble sharing a common frequency-sparse component from the collection of their compressed measurements. Unlike conventional arts in compressed sensing, the frequencies follow an off-the-grid formulation and are continuously valued in [0, 1]. As an extension of atomic norm, the concatenated atomic norm minimization approach is proposed to handle the exact recovery of signals, which is reformulated as a computationally tractable semidefinite program. The optimality of the proposed approach is characterized using a dual certificate. Numerical experiments are performed to illustrate the effectiveness of the proposed approach and its advantage over separate recovery.
Keywords :
compressed sensing; mathematical programming; minimisation; common frequency-sparse component; compressed measurement; concatenated atomic norm minimization approach; distributed compressed sensing; dual certificate characterization; frequency-sparse signal ensemble joint recovery; off-the-grid formulation; semidefinite program; Atomic clocks; Compressed sensing; Frequency measurement; Joints; Minimization; Polynomials; Signal resolution; Atomic norm; basis mismatch; compressed sensing; joint sparsity; semidefinite program;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2014.2349904
Filename :
6880754
Link To Document :
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