Bayesian Sparse Fourier Representation of Off-Grid Targets

Marie Lasserre (1) , Stéphanie Bidon (1) , Olivier Besson (1) , François Le Chevalier (2)

1 DEOS - Département Electronique, Optronique et Signal
2 TU Delft - Delft University of Technology

We consider the problem of estimating a finite sum of cisoids via the use of a sparsifying Fourier dictionary (problem that may be of use in many radar applications). Numerous signal sparse representation (SSR) techniques can be found in the literature regarding this problem. However, they are usually very sensitive to grid mismatch. In this paper, we present a new Bayesian model robust towards grid mismatch. Synthetic and experimental radar data are used to assess the ability of the proposed approach to robustify the SSR towards grid mismatch.

Mots clés: Sparse representation (SSR); Grid mismatch; Bayesian inference

Domaines: Traitement du signal et de l'image [eess.SP]

Marie Lasserre, Stéphanie Bidon, Olivier Besson, François Le Chevalier. Bayesian Sparse Fourier Representation of Off-Grid Targets. International Radar Conference (Radar 2014), Oct 2014, Lille, France. pp.1-6, ⟨10.1109/RADAR.2014.7060282⟩. ⟨hal-01333511⟩