Sparsity and Compressed Sensing in Radar Imaging

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Compressive Sensing in Electromagnetics - A Review (2015, methodology): “Analogously to inverse scattering, the simplest model of the reflected radar signal for adapting the nonlinear formulation at hand to the CS framework is based on the BA applied to the free-space propagation of narrowband plane waves impinging on slow targets located in the far field [16].”
Reward Estimation for Variance Reduction in Deep Reinforcement Learning (2018, background): “This may reflect a scenario where there is a signal dropout either in a sensory-based reward signal as in [36] or in communication of the reward signal.”
Microwave Imaging Within the First-Order Born Approximation by Means of the Contrast-Field Bayesian Compressive Sensing (2012, methodology): “Thanks to these features, CS techniques have been already employed for solving electromagnetic inverse problems arising in radar [45], magnetic resonance [46], and terahertz applications [47].”