Modeling and simulation of the fused Bayesian-regularization method for remote sensing imagery with synthetic aperture arrays

A new fused Bayesian regularization (FBR) method for enhanced remote sensing imaging based on a new concept of aggregated statistical-deterministic regularization was developed recently. In this study, we represent the results of modeling and extensive simulation of the FBR algorithms for enhanced reconstruction of the spatial spectrum patterns (SSP) of the point-type and spatially distributed wavefield sources as it is required for the remote sensing imagery with synthetic aperture arrays. The simulations were performed in the MATLAB computational environment for the family of the SAR imaging algorithms that employed different modifications of the FBR method. The presented results enable one to evaluate the operational performance of the FBR method that was not previously reported in the literature.