Joint recovery of sparse signals and parameter perturbations with parameterized measurement models

Erik C. Johnson, Douglas L Jones

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many applications involve sparse signals with unknown, continuous parameters; a common example is a signal consisting of several sinusoids of unknown frequency. Applying compressed sensing techniques to these signals requires a highly oversampled dictionary for good approximation, but these dictionaries violate the RIP conditions and produce inconsistent results. We consider recovering both a sparse vector and parameter perturbations from an initial set of parameters. Joint recovery allows for accurate reconstructions without highly oversampled dictionaries. Our algorithm for sparse recovery solves a series of linearized subproblems. Recovery error for noiseless simulated measurements is near zero for coarse dictionaries, but increases with the oversampling. This technique is also used to reconstruct Radio Frequency data. The algorithm estimates sharp peaks and transmitter frequencies, demonstrating the potential practical use of the algorithm on real data.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages5900-5904
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period5/26/135/31/13

Fingerprint

Glossaries
Recovery
Compressed sensing
Transmitters

Keywords

  • Frequency Estimation
  • Parameter Perturbations
  • Parameterized Model
  • Sparse Reconstruction
  • Sparse Signal

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Johnson, E. C., & Jones, D. L. (2013). Joint recovery of sparse signals and parameter perturbations with parameterized measurement models. In 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings (pp. 5900-5904). [6638796] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2013.6638796

Joint recovery of sparse signals and parameter perturbations with parameterized measurement models. / Johnson, Erik C.; Jones, Douglas L.

2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings. 2013. p. 5900-5904 6638796 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Johnson, EC & Jones, DL 2013, Joint recovery of sparse signals and parameter perturbations with parameterized measurement models. in 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings., 6638796, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 5900-5904, 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, 5/26/13. https://doi.org/10.1109/ICASSP.2013.6638796
Johnson EC, Jones DL. Joint recovery of sparse signals and parameter perturbations with parameterized measurement models. In 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings. 2013. p. 5900-5904. 6638796. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2013.6638796
Johnson, Erik C. ; Jones, Douglas L. / Joint recovery of sparse signals and parameter perturbations with parameterized measurement models. 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings. 2013. pp. 5900-5904 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).
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