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Extraction of Weak Target Features from Radar Tomographic Imagery

Almutiry, Muhannad Salem S.
http://orcid.org/0000-0002-3862-3129
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1470154676

Abstract Details

2016, Doctor of Philosophy (Ph.D.), University of Dayton, Electrical Engineering.
Radio Frequency (RF) Tomography is a mathematical process of 3D image reconstruction from a measurement using a multistatic distribution of transmitters and receivers. The geometric diversity of these elements increases the information in the measurements. The process of determining the permittivity and conductivity profile in the measurement domain, and, therefore, the shape of the target, from the scattered field measurements, is an inverse problem. To solve this problem, under conventional methods such as the Born approximation, we use the principles of linear scattering to determine a linear relationship between measured returns and target shape. The Born approximation is valid if the scatterer is small and does not interact strongly with other objects. However, strong scatterers within the domain may generate sidelobes masking weaker returns. This masking, in conjunction with multipath effects, may result in loss of features and subsequent failure to identify a target. In this research, a novel method is proposed to increase overall image quality and extend the capabilities of RF tomography by modeling the strong scatterers in the measurement domain as dipoles that behave as secondary sources (transmitters). Unlike conventional methods, the dipole model reduces the effects of the sidelobes from the strong scatterers and exploits the multipath of multiple targets or complex shapes. The multipath phenomena contains more information about the targets permitting illumination in the shadowed region and an increase to the radar aperture length. The electromagnetic characteristics for each modeled dipole are estimated by representing the cells in the measurement domain's image. The eigenvalue and eigenvector from each cell represent the phase and magnitude for the modeled dipole and also the spatial orientation of the target. The process of modeling large scatterers as dipoles can be iterated, addressing one strong scatterer at a time. This method effectively suppresses the sidelobes and exploits the multipath within the measurement domain. Using the Born approximation, the linear relationship between the scattered fields and the target is updated for simplicity. With iterations, the “extra” dipole will account for the multipath effects, thus removing some limitations caused by the Born approximation. This concept has been successfully demonstrated in software (FEKO© by Altair). In addition, this work also presents an innovative conversion using a back-projection algorithm for multipath effects and modeling of an “additional” source or transmitter in the measurement domain. The result of implementing this method of modeling strong scatterers as dipoles successfully demonstrated an increase in the resolution and enhanced radar imagery.
Michael Wicks (Advisor)
Keigo Hirakawa (Committee Member)
John Loomis (Committee Member)
Lorenzo Lo Monte (Committee Member)
109 p.
Electrical Engineering
Born Approximation; Radar imaging; synthetic aperture radar; Microwave imaging; ground penetrating radar; Radio frequency tomography

Recommended Citations

Citations

  • Almutiry, M. S. S. (2016). Extraction of Weak Target Features from Radar Tomographic Imagery [Doctoral dissertation, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1470154676

    APA Style (7th edition)

  • Almutiry, Muhannad. Extraction of Weak Target Features from Radar Tomographic Imagery. 2016. University of Dayton, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1470154676.

    MLA Style (8th edition)

  • Almutiry, Muhannad. "Extraction of Weak Target Features from Radar Tomographic Imagery." Doctoral dissertation, University of Dayton, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1470154676

    Chicago Manual of Style (17th edition)

dayton1470154676
578
© 2016, some rights reserved.Creative Commons License Extraction of Weak Target Features from Radar Tomographic Imagery by Muhannad Salem S. Almutiry is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Dayton and OhioLINK.