Abstract

Perhaps the largest obstacle to practical compressive sampling is an inability to accurately, and sparsely describe the data one seeks to recover due to poor choice of signal model parameters. In such cases the recovery process will yield artifacts, or in many cases, fail completely. This work represents the first demonstration of a solution to this so-called "off-grid" problem in an experimental, compressively sampled system. Specifically, we show that an Alternating Convex Search algorithm is able to significantly reduce these data model errors in harmonic signal recovery.

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