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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.
Cited literature [2 references]
https://hal.inria.fr/hal-00751360
Contributor : Cagdas Bilen <>
Submitted on : Tuesday, November 13, 2012 - 11:46:41 AM
Last modification on : Tuesday, June 15, 2021 - 4:11:16 PM
Long-term archiving on: : Thursday, February 14, 2013 - 3:41:12 AM
Contributor : Cagdas Bilen <>
Submitted on : Tuesday, November 13, 2012 - 11:46:41 AM
Last modification on : Tuesday, June 15, 2021 - 4:11:16 PM
Long-term archiving on: : Thursday, February 14, 2013 - 3:41:12 AM
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