Phaseless Parametric Inversion for System Calibration and Obtaining Prior Information

Electromagnetic inversion systems require that the experimental data be calibrated to the computational inversion model being used. In addition, accurate prior information provided to the inversion algorithm leads to higher-quality images. For some applications of inversion, such as stored grain ima...

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Main Authors: Colin Gilmore, Ian Jeffrey, Mohammad Asefi, Nicholas T. Geddert, Kevin G. Brown, Joe Lovetri
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8825792/
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spelling doaj-5bf4f079c10d4e94b108a3139df093552021-03-29T23:38:37ZengIEEEIEEE Access2169-35362019-01-01712873512874510.1109/ACCESS.2019.29397258825792Phaseless Parametric Inversion for System Calibration and Obtaining Prior InformationColin Gilmore0https://orcid.org/0000-0002-6958-3545Ian Jeffrey1https://orcid.org/0000-0003-1312-3248Mohammad Asefi2Nicholas T. Geddert3Kevin G. Brown4Joe Lovetri5Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, CanadaDepartment of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, Canada151 Research, Inc., Winnipeg, MB, Canada151 Research, Inc., Winnipeg, MB, Canada151 Research, Inc., Winnipeg, MB, CanadaDepartment of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, CanadaElectromagnetic inversion systems require that the experimental data be calibrated to the computational inversion model being used. In addition, accurate prior information provided to the inversion algorithm leads to higher-quality images. For some applications of inversion, such as stored grain imaging or geophysical inversion, known (calibration) targets cannot be easily introduced into the imaging region and the ability to determine prior information can be limited. In an attempt to solve the problem of calibrating data from such field-inversion systems, we introduce a work flow where: (1) a simple parametric physical model of the scattering background is obtained via a phaseless (magnitude only data) inversion algorithm that works on phase-corrupted, uncalibrated total-field measurements, and (2) we then use this simple physical model to generate calibration and prior information for subsequent full-data (magnitude and phase) inversion. Using an example of in-bin stored grain imaging, the inverted parameters are the grain angle of repose, grain height, and the average bulk permittivity of the grain. Using uncalibrated total-field data, we show that the proposed work flow obtains the overall structure of the grain in a bin despite the use of this raw data. We then show that the simple physical model can be used as both a calibration data set as well as the prior information about the grain target in a full-data (magnitude and phase) inversion. The use of this phaseless algorithm means we are able to remotely calibrate imaging systems, and obtain critical prior information about the imaging region without introducing a calibration target or physically measuring the imaging region in other ways.https://ieeexplore.ieee.org/document/8825792/Inverse problemscalibrationmicrowave tomographyinverse imaging
collection DOAJ
language English
format Article
sources DOAJ
author Colin Gilmore
Ian Jeffrey
Mohammad Asefi
Nicholas T. Geddert
Kevin G. Brown
Joe Lovetri
spellingShingle Colin Gilmore
Ian Jeffrey
Mohammad Asefi
Nicholas T. Geddert
Kevin G. Brown
Joe Lovetri
Phaseless Parametric Inversion for System Calibration and Obtaining Prior Information
IEEE Access
Inverse problems
calibration
microwave tomography
inverse imaging
author_facet Colin Gilmore
Ian Jeffrey
Mohammad Asefi
Nicholas T. Geddert
Kevin G. Brown
Joe Lovetri
author_sort Colin Gilmore
title Phaseless Parametric Inversion for System Calibration and Obtaining Prior Information
title_short Phaseless Parametric Inversion for System Calibration and Obtaining Prior Information
title_full Phaseless Parametric Inversion for System Calibration and Obtaining Prior Information
title_fullStr Phaseless Parametric Inversion for System Calibration and Obtaining Prior Information
title_full_unstemmed Phaseless Parametric Inversion for System Calibration and Obtaining Prior Information
title_sort phaseless parametric inversion for system calibration and obtaining prior information
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description Electromagnetic inversion systems require that the experimental data be calibrated to the computational inversion model being used. In addition, accurate prior information provided to the inversion algorithm leads to higher-quality images. For some applications of inversion, such as stored grain imaging or geophysical inversion, known (calibration) targets cannot be easily introduced into the imaging region and the ability to determine prior information can be limited. In an attempt to solve the problem of calibrating data from such field-inversion systems, we introduce a work flow where: (1) a simple parametric physical model of the scattering background is obtained via a phaseless (magnitude only data) inversion algorithm that works on phase-corrupted, uncalibrated total-field measurements, and (2) we then use this simple physical model to generate calibration and prior information for subsequent full-data (magnitude and phase) inversion. Using an example of in-bin stored grain imaging, the inverted parameters are the grain angle of repose, grain height, and the average bulk permittivity of the grain. Using uncalibrated total-field data, we show that the proposed work flow obtains the overall structure of the grain in a bin despite the use of this raw data. We then show that the simple physical model can be used as both a calibration data set as well as the prior information about the grain target in a full-data (magnitude and phase) inversion. The use of this phaseless algorithm means we are able to remotely calibrate imaging systems, and obtain critical prior information about the imaging region without introducing a calibration target or physically measuring the imaging region in other ways.
topic Inverse problems
calibration
microwave tomography
inverse imaging
url https://ieeexplore.ieee.org/document/8825792/
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