Skip to Main content Skip to Navigation
Documents associated with scientific events

Blind Sensor Calibration in Sparse Recovery

Abstract : We consider the problem of calibrating a compressed sensing measurement system under the assumption that the decalibration consists of unknown complex gains on each measure. We focus on {\em blind} calibration, using measures performed on a few unknown (but sparse) signals. In the considered context, we study several sub-problems and show that they can be formulated as convex optimization problems, which can be solved easily using off-the-shelf algorithms. Numerical simulations demonstrate the effectiveness of the approach even for highly uncalibrated measures, when a sufficient number of (unknown, but sparse) calibrating signals is provided.
Document type :
Documents associated with scientific events
Complete list of metadata

Cited literature [2 references]  Display  Hide  Download
Contributor : Cagdas Bilen Connect in order to contact the contributor
Submitted on : Tuesday, November 13, 2012 - 11:46:41 AM
Last modification on : Sunday, June 26, 2022 - 2:18:36 AM
Long-term archiving on: : Thursday, February 14, 2013 - 3:41:12 AM


Files produced by the author(s)


  • HAL Id : hal-00751360, version 1


Cagdas Bilen, Gilles Puy, Rémi Gribonval, Laurent Daudet. Blind Sensor Calibration in Sparse Recovery. international biomedical and astronomical signal processing (BASP) Frontiers workshop, Jan 2013, Villars-sur-Ollon, Switzerland. ⟨hal-00751360⟩



Record views


Files downloads