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High-resolution imaging with uncertain radar measurement data: A doubly regularized compressive sensing experiment design approach

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4 Author(s)
Y. Shkvarko ; Department of Telecommunications, Center for Advanced Research and Education of the National Polytechnic Institute, CINVESTAV-IPN, Guadalajara, Mexico ; J. Tuxpan ; S. Santos ; Israel Yañez

The descriptive experiment design regularization (DEDR) paradigm is aggregated with the variational analysis approach that combines the ℓ2 image metric with the ℓ1 sparse image gradient map metric structures in the solution space. The proposed ℓ2 - ℓ1 structured total variation DEDR (TV-DEDR) framework is particularly adapted for enhanced imaging with low resolution side looking airborne radar/fractional SAR sensors putting in a single optimization frame adaptive SAR image despeckling and resolution enhancement that exploits the structured desired image sparseness properties. The TV-DEDR method implemented in an implicit contractive mapping iterative fashion outperforms the competing nonparametric adaptive radar imaging techniques both in the resolution enhancement and computational complexity as verified in the simulations.

Published in:

2012 IEEE International Geoscience and Remote Sensing Symposium

Date of Conference:

22-27 July 2012