Ground penetrating radar (GPR) represents a promising technology for the non-invasive exploration of soil and for the quantitative characterization and localization of buried objects. Unfortunately, this technique suffers for some limitations, among which the high number of data required for the processing of GPR information. In order to overcome this drawback, the paper proposes a mixed-norm approach based on the combination of compressive sensing (CS) theory and Wavelet decomposition basis to enhance signal processing and meantime to reduce the number of data required for the inversion procedure. The accuracy of the proposed approach is validated by means of a numerical analysis carried out in simplified two-dimensional (2D) scenarios.
A mixed L2- L1norm minimization procedure for the data processing of ground penetrating radar
Ambrosanio, Michele
;Schirinzi, Gilda;Pascazio, Vito
2017-01-01
Abstract
Ground penetrating radar (GPR) represents a promising technology for the non-invasive exploration of soil and for the quantitative characterization and localization of buried objects. Unfortunately, this technique suffers for some limitations, among which the high number of data required for the processing of GPR information. In order to overcome this drawback, the paper proposes a mixed-norm approach based on the combination of compressive sensing (CS) theory and Wavelet decomposition basis to enhance signal processing and meantime to reduce the number of data required for the inversion procedure. The accuracy of the proposed approach is validated by means of a numerical analysis carried out in simplified two-dimensional (2D) scenarios.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
