Spectral Compressive Sensing with Polar Interpolation

Karsten Fyhn, Hamid Dadkhahi, Marco F. Duarte

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18 Citationer (Scopus)
380 Downloads (Pure)

Abstrakt

Existing approaches to compressive sensing of frequency-sparse signals focuses on signal recovery rather than spectral estimation. Furthermore, the recovery performance is limited by the coherence of the required sparsity dictionaries and by the discretization of the frequency parameter space. In this paper, we introduce a greedy recovery algorithm that leverages a band-exclusion function and a polar interpolation function to address these two issues in spectral compressive sensing. Our algorithm is geared towards line spectral estimation from compressive measurements and outperforms most existing approaches in fidelity and tolerance to noise.
OriginalsprogEngelsk
TitelProceedings of the 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) : ICASSP
ForlagIEEE Press
Publikationsdato2013
Sider6225-6229
ISBN (Trykt)9781479903573
ISBN (Elektronisk)978-1-4799-0356-6, 9781479903559
StatusUdgivet - 2013
Begivenhed2013 IEEE International Conference on Acoustics, Speech, and Signal Processing - Vancouver, Canada
Varighed: 26 maj 201331 maj 2013
Konferencens nummer: 38

Konference

Konference2013 IEEE International Conference on Acoustics, Speech, and Signal Processing
Nummer38
LandCanada
ByVancouver
Periode26/05/201331/05/2013
NavnI E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN1520-6149

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