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Wideband electromagnetic induction (WEMI) sensors are used to detect, classify, and locate obscured targets. WEMI sensors can be designed to measure the magnetic fields either in the time domain or frequency domain. They also capture multiple location measurements from a target by either a physical sensor array, a synthetic sensor array created by scanning the sensor, or a combination of the two....
This work presents a mathematical approach for recovering a physical model from a low-rank approximation of measured data obtained via the singular value decomposition (SVD). The general form of a low-rank physical model of the data is often known, so the presented approach learns the proper rotation and scaling matrices from the singular vectors and singular values of the SVD in order to recover...
This work focuses on parametric sparse sensing models and looks to improve ℓ1 regularization results when the model dictionary is strongly coherent and/or regularization parameters are unknown. The singular value decomposition (SVD) of the model's dictionary matrix is used to construct signal and noise subspaces. A method that uses the measurements to automatically optimize the subspace division along...
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