A Hybrid Qualitative-Quantitative Electromagnetic Imaging Method for Subsurface Prospecting

被引：0

作者：

Schenone, Valentina ^{[1
]}

Fedeli, Alessandro ^{[1
]}

Pastorino, Matteo ^{[1
]}

Randazzo, Andrea ^{[1
]}

Estatico, Claudio ^{[2
]}

机构：

[1] Univ Genoa, Dept Elect Elect Telecommun Engn & Naval Architec, Genoa, Italy

[2] Univ Genoa, Dept Math, Genoa, Italy

来源：

2022 IEEE INTERNATIONAL CONFERENCE ON IMAGING SYSTEMS AND TECHNIQUES (IST 2022) | 2022年

关键词：

Electromagnetic imaging; inverse scattering; Ground Penetrating Radar; Lebesgue spaces; INVERSE SCATTERING PROBLEMS; LEBESGUE-SPACE INVERSION; MICROWAVE; RECONSTRUCTION; TARGETS; RADAR;

D O I：

10.1109/IST55454.2022.9827669

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the present paper, a hybrid electromagnetic imaging method for subsurface prospection is presented. The approach is based on the cascade of two blocks: a time- domain qualitative reconstruction algorithm followed by a multi frequency quantitative inverse-scattering technique. In the first phase, the scattered-field data estimated by adaptive filtering are exploited by a beamforming method to produce an initial image of buried targets. In the second phase, a multifrequency inexact-Newton inversion approach developed in Lebesgue spaces with variable exponents uses the first-step image in two different qualitative-quantitative combination strategies: as a priori information for setting the exponent function and to weight the solution updates inside the iterative inversion procedure. The approach has been validated using numerically simulated scattered-field data. An analysis on the effects of the application of the two qualitative-quantitative combination strategies is presented.

引用

页数：6

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