A COMPRESSIVE SENSING BASED APPROACH FOR MICROWAVE TOMOGRAPHY AND GPR APPLICATIONS

被引：9

作者：

Ambrosanio, Michele ^{[1
]}

Autieri, Roberta ^{[1
]}

Pascazio, Vito ^{[1
]}

机构：

[1] Univ Napoli Parthenope, Ctr Direz Napoli, Dipartimento Ingn, I-80143 Naples, Italy

来源：

2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年

关键词：

Microwave tomography; electromagnetic inverse scattering; ground penetrating radar; compressive sensing;

D O I：

10.1109/IGARSS.2014.6947144

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

It is well-known that in a canonical inverse scattering problem there is only a limited amount of independent data which is quantified by the degree of freedom of the problem one is dealing with. Of course, it is mandatory, in order to recover the signal in a proper way, to sample the data at least at Nyquist rate. However, there are some cases in which the number of independent data of a signal is much smaller than what its bandwidth seems to suggest, and in these situations the theory of Compressive Sensing may help to improve reconstruction capabilities without using so much information. In this framework, the following communication deals with a preliminary analysis of the solution of microwave imaging problems by exploiting the theory of Compressive Sensing in a linearized multiview-multistatic single-frequency approach.

引用

页数：4

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