Detection of the Cavities Inside a Target with Near Field Orthogonality Sampling Method

Mehmet Nuri Akinci*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this contribution, a recently proposed qualitative imaging technique, Near Field Orthogonality Sampling Method, is applied to screen the cavities inside a target. For this aim, the scattered field measurements from the targets are simulated at microwave frequency range. The obtained data is corrupted with additive white Gaussian noise (AWGN) to prevent any inverse crime. After, assuming that the outer shape and average electrical properties of the scatterer is known, the background data is subtracted from the noisy measurements. Then, obtained difference is directly applied to NOSM algorithm. The interesting properties of the method are in order: (i) the NOSM can operate with a single view - multi static measurement configuration; (ii) the multi-frequency data can be easily integrated into calculation process due to qualitative nature of the proposed method. Obtained results show the usefulness of the NOSM in nondestructive testing applications.

Original languageEnglish
Title of host publication2018 18th Mediterranean Microwave Symposium, MMS 2018
PublisherIEEE Computer Society
Pages391-393
Number of pages3
ISBN (Electronic)9781538671320
DOIs
Publication statusPublished - 2 Jul 2018
Event18th Mediterranean Microwave Symposium, MMS 2018 - Istanbul, Turkey
Duration: 31 Oct 20182 Nov 2018

Publication series

NameMediterranean Microwave Symposium
Volume2018-October
ISSN (Print)2157-9822
ISSN (Electronic)2157-9830

Conference

Conference18th Mediterranean Microwave Symposium, MMS 2018
Country/TerritoryTurkey
CityIstanbul
Period31/10/182/11/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Fingerprint

Dive into the research topics of 'Detection of the Cavities Inside a Target with Near Field Orthogonality Sampling Method'. Together they form a unique fingerprint.

Cite this