Image processing and data analysis: the multiscale approach
Image processing and data analysis: the multiscale approach
Radar Systems Analysis and Design Using MATLAB
Radar Systems Analysis and Design Using MATLAB
IEEE Transactions on Signal Processing
Theoretical aspects of radar imaging using stochastic waveforms
IEEE Transactions on Signal Processing
General choice of the regularization functional in regularized image restoration
IEEE Transactions on Image Processing
Regularized constrained total least squares image restoration
IEEE Transactions on Image Processing
Intelligent Experiment Design-Based Virtual Remote Sensing Laboratory
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
EURASIP Journal on Advances in Signal Processing
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We address a new approach to solve the ill-posed nonlinear inverse problem of high-resolution numerical reconstruction of the spatial spectrum pattern (SSP) of the backscattered wavefield sources distributed over the remotely sensed scene. An array or synthesized array radar (SAR) that employs digital data signal processing is considered. By exploiting the idea of combining the statistical minimum risk estimation paradigm with numerical descriptive regularization techniques, we address a new fused statistical descriptive regularization (SDR) strategy for enhanced radar imaging. Pursuing such an approach, we establish a family of the SDR-related SSP estimators, that encompass a manifold of existing beamforming techniques ranging from traditional matched filter to robust and adaptive spatial filtering, and minimum variance methods.