Convex Optimization Approaches for Blind Sensor Calibration using Sparsity - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Preprints, Working Papers, ... Year :

Convex Optimization Approaches for Blind Sensor Calibration using Sparsity


We investigate a compressive sensing framework in which the sensors introduce a distortion to the measurements in the form of unknown gains. We focus on {\em blind} calibration, using measures performed on {\em multiple} unknown (but sparse) signals and formulate the joint recovery of the gains and the sparse signals as a convex optimization problem. We divide this problem in 3 subproblems with different conditions on the gains, specifially (i) gains with different amplitude and the same phase, (ii) gains with the same amplitude and different phase and (iii) gains with different amplitude and phase. In order to solve the first case, we propose an extension to the basis pursuit optimization which can estimate the unknown gains along with the unknown sparse signals. For the second case, we formulate a quadratic approach that eliminates the unknown phase shifts and retrieves the unknown sparse signals. An alternative form of this approach is also formulated to reduce the complexity and memory requirements and provide scalability with respect to the number of input signals. Finally for the the third case, we propose a formulation that combines the earlier two approaches to solve the problem. The performance of the proposed algorithms is investigated extensively through numerical simulations, which demonstrate that simultaneous signal recovery and calibration is possible with convex methods when sufficiently many (unknown, but sparse) calibrating signals are provided.
Fichier principal
Vignette du fichier
JoSP_draft_v2.pdf (402.19 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-00853225 , version 1 (22-08-2013)
hal-00853225 , version 2 (24-08-2013)
hal-00853225 , version 3 (17-03-2014)
hal-00853225 , version 4 (19-03-2014)
hal-00853225 , version 5 (22-07-2014)
hal-00853225 , version 6 (25-08-2014)



Cagdas Bilen, Gilles Puy, Rémi Gribonval, Laurent Daudet. Convex Optimization Approaches for Blind Sensor Calibration using Sparsity. 2014. ⟨hal-00853225v4⟩
1034 View
759 Download



Gmail Facebook Twitter LinkedIn More