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• W3104684837 endingPage "115002" @default.
• W3104684837 startingPage "115002" @default.
• W3104684837 abstract "The design of high-precision sensing devises becomes ever more difficult and expensive. At the same time, the need for precise calibration of these devices (ranging from tiny sensors to space telescopes) manifests itself as a major roadblock in many scientific and technological endeavors. To achieve optimal performance of advanced high-performance sensors one must carefully calibrate them, which is often difficult or even impossible to do in practice. In this work we bring together three seemingly unrelated concepts, namely self-calibration, compressive sensing, and biconvex optimization. The idea behind self-calibration is to equip a hardware device with a smart algorithm that can compensate automatically for the lack of calibration. We show how several self-calibration problems can be treated efficiently within the framework of biconvex compressive sensing via a new method called SparseLift. More specifically, we consider a linear system of equations where both and the diagonal matrix (which models the calibration error) are unknown. By 'lifting' this biconvex inverse problem we arrive at a convex optimization problem. By exploiting sparsity in the signal model, we derive explicit theoretical guarantees under which both and can be recovered exactly, robustly, and numerically efficiently via linear programming. Applications in array calibration and wireless communications are discussed and numerical simulations are presented, confirming and complementing our theoretical analysis." @default.
• W3104684837 created "2020-11-23" @default.
• W3104684837 creator A5047770219 @default.
• W3104684837 creator A5080565728 @default.
• W3104684837 date "2015-09-30" @default.
• W3104684837 modified "2023-09-27" @default.
• W3104684837 title "Self-calibration and biconvex compressive sensing" @default.
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• W3104684837 doi "https://doi.org/10.1088/0266-5611/31/11/115002" @default.
• W3104684837 hasPublicationYear "2015" @default.
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