Compressive sensing for sensor calibration

Volkan Cevher, Richard Baraniuk

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

10 Scopus citations

Abstract

We consider a calibration problem, where we determine an unknown sensor location using the known track of a calibration target and a known reference sensor location. We cast the calibration problem as a sparse approximation problem where the unknown sensor location is determined over a discrete spatial grid with respect to the reference sensor. To achieve the calibration objective, low dimensional random projections of the sensor data are passed to the reference sensor, which significantly reduces the inter-sensor communication bandwidth. The unknown sensor location is then determined by solving an ℓ1-norm minimization problem (linear program). Field data results are provided to demonstrate the effectiveness of the approach.

Original languageEnglish (US)
Title of host publicationSAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop
Pages175-178
Number of pages4
DOIs
StatePublished - 2008
EventSAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop - Darmstadt, Germany
Duration: Jul 21 2008Jul 23 2008

Publication series

NameSAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop

Other

OtherSAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop
CountryGermany
CityDarmstadt
Period7/21/087/23/08

Keywords

  • Direction-of-arrival estimation
  • Microphone arrays
  • Sensor networks

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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