Abstract
A new methodology that exploits the matrix completion (MC) paradigm is proposed to image weak and sparse scatterers in heavy noise conditions. The 2-D inverse problem, mathematically formulated under the first-order Born approximation, is addressed with a three-phase algorithm that consists of: 1) an initial estimation step where a preliminary reconstruction of the distribution of the contrast and the associated “confidence map” are computed by means of a Bayesian compressive sensing method; 2) a filtering step devoted to identify and discard the less reliable contrast coefficients; and 3) a final dielectric profile completion step aimed at recovering a faithful image of the whole scattering scenario by exploiting a customized MC procedure. Representative numerical results and comparisons with competitive state-of-the-art inversion techniques are reported and discussed to assess the accuracy, the robustness, and the numerical efficiency of the proposed approach.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Microwave Theory and Techniques
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
