Microwave Imaging Within the First-Order Born Approximation by Means of the Contrast-Field Bayesian Compressive Sensing

@article{Poli2012MicrowaveIW,
  title={Microwave Imaging Within the First-Order Born Approximation by Means of the Contrast-Field Bayesian Compressive Sensing},
  author={Lorenzo Poli and Giacomo Oliveri and Andrea Massa},
  journal={IEEE Transactions on Antennas and Propagation},
  year={2012},
  volume={60},
  pages={2865-2879}
}
A new approach based the contrast field (CF) formulation of the microwave imaging problem that exploits the Bayesian compressive sampling (BCS) paradigm is proposed for the reconstruction of sparse distributions of weak scatterers. Towards this end, the original inverse scattering problem is recast to a probabilistic sparseness constrained optimization by introducing suitable hierarchical priors as sparsity constraints. A fast relevance vector machine (RVM) is then employed to reconstruct the… CONTINUE READING
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