In this article, a matching pursuit algorithm is developed to improve the performance of a passive multiplexing technique based on compressed sensing. This deconvolution technique is applied to RADAR imaging in the microwave range, starting from previous studies based on a compact coding device and L1-norm regularizations. This study demonstrates that in this context, the quality of the reconstructed RADAR images can be improved using an algorithm close to Hogbom's Clean, and based on a dictionary built with Tikhonov pseudo-inversions. The theoretical principle of this new algorithm is developed, followed by a parameters study. Finally, an experimental validation is presented to demonstrate the efficiency of this iterative algorithm.
"Clean Deconvolution Applied to Passive Compressed Beamforming," Progress In Electromagnetics Research C,
Vol. 56, 163-172, 2015. doi:10.2528/PIERC15011804
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