Blind Sensor Calibration in Sparse Recovery - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Documents Associated With Scientific Events Year : 2013

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.
Fichier principal
Vignette du fichier
abstract.pdf (78.27 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00751360 , version 1 (13-11-2012)

Identifiers

  • HAL Id : hal-00751360 , version 1

Cite

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⟩
837 View
111 Download

Share

Gmail Facebook X LinkedIn More