Multiplexed Compressed Sensing for general frequency sparse signals

Compressed Sensing algorithms have provided feasible and reasonably accurate solutions to the problem of reconstructing signals of which only sub-Nyquist number of samples have been acquired. A framework called MOSAICS for acquiring multiple analog channels using limited number of A/D converters by...

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Bibliographic Details
Main Authors: Satyanarayana, J V, Ramakrishnan, A G
Format: Conference Proceeding
Language:English
Subjects:
A/D Conversion
Analytical models
Bandlimited signals
Compressed Sensing
Frequency measurement
Image reconstruction
Multiplexing
MUSIC
Nyquist sampling theorem
Real time
Signal reconstruction
Spectral Compressed Sensing
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Summary:Compressed Sensing algorithms have provided feasible and reasonably accurate solutions to the problem of reconstructing signals of which only sub-Nyquist number of samples have been acquired. A framework called MOSAICS for acquiring multiple analog channels using limited number of A/D converters by exploiting CS based undersampling has been proposed in our previous work. In this paper we introduce an improvised reconstruction algorithm into the MOSAICS scheme, which overcomes a limitation in MOSAICS, thereby being able to handle a wider class of signals.
DOI:10.1109/ICCSP.2011.5739351