DocumentCode :
631134
Title :
Signal sensing by multiple compressive projection measurement
Author :
Yun Lu ; Statz, Christoph ; Hegler, Sebastian ; Plettemeier, Dirk
Author_Institution :
Tech. Univ. Dresden, Dresden, Germany
Volume :
1
fYear :
2013
fDate :
19-21 June 2013
Firstpage :
101
Lastpage :
106
Abstract :
Compressive sensing (CS) is a new approach to simultaneous sensing and compression that enables a potentially large reduction in the sampling of signals having a sparse representation in some basis. However, the most recent recovery algorithms are successful only under condition of an acceptable signal to noise ratio (SNR). In this paper we will analyze and discuss sparse signal recovery for the low-SNR case by introducing the multiple compressive projection measurement approach (MCPM). First results show that MCPM is a very promising method to enhance the recovery stability with presence of strong background noise.
Keywords :
compressed sensing; signal sampling; CS; MCPM; compressive sensing; low-SNR case; multiple compressive projection measurement approach; signal sampling; signal sensing; signal to noise ratio; sparse representation; sparse signal recovery; Delay effects; Estimation; Noise measurement; Signal to noise ratio; Sparks; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar Symposium (IRS), 2013 14th International
Conference_Location :
Dresden
Print_ISBN :
978-1-4673-4821-8
Type :
conf
Filename :
6581071
Link To Document :
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