In this work, an overview of the main concepts when using Compressive Processing (CP)-based methods for microwave imaging is reported. The main theoretical aspects and conditions, namely the sparseness of the unknowns with respect to the representative basis and the incoherence of the measured data encoded within the Restrict Isometry Property (RIP) of the problem matrix linking the data to the unknowns, are provided, enabling the use of efficient CP inversion tools. Simple examples are reported, aimed at illustrating the effectiveness of the presented theory.
Advanced Microwave Imaging with Compressive Processing - Concepts, Methods, and Applications / Massa, A.; Anselmi, N.; Oliveri, G.; Salucci, M.. - STAMPA. - (2019), pp. 1-4. (Intervento presentato al convegno COMCAS 2019 tenutosi a Tel Aviv, Israel nel 4th-6th November 2019) [10.1109/COMCAS44984.2019.8958087].
Advanced Microwave Imaging with Compressive Processing - Concepts, Methods, and Applications
Massa A.;Anselmi N.;Oliveri G.;Salucci M.
2019-01-01
Abstract
In this work, an overview of the main concepts when using Compressive Processing (CP)-based methods for microwave imaging is reported. The main theoretical aspects and conditions, namely the sparseness of the unknowns with respect to the representative basis and the incoherence of the measured data encoded within the Restrict Isometry Property (RIP) of the problem matrix linking the data to the unknowns, are provided, enabling the use of efficient CP inversion tools. Simple examples are reported, aimed at illustrating the effectiveness of the presented theory.| File | Dimensione | Formato | |
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