Master of Science, The Ohio State University, 2020, Electrical and Computer Engineering

As an emerging area of research, near-field microwave imaging has elicited considerable interest. The remarkable properties of microwaves and the convenience of portable imaging systems make this technology attractive in various application areas. This thesis conducts the comparison between coherent and incoherent imaging algorithms: back projection algorithm, interferometric imaging algorithm and self-correlation back projection algorithm for the near field circumstance. Near-field interferometric imaging is a relatively new incoherent approach that can use virtually any microwave source of opportunity rather than a conventional radar transmitter. A thorough comparison with the coherent back projection approaches has not been previously conducted. Notwithstanding merits of microwave imaging, the microwave frequency band is vulnerable to the environment. In addition, the received signal is mixed with the inevitable Direct Path Interference (DPI) from transmitter during the detection process. The DPI signal can be orders of magnitude stronger than the echo signals from the targets of interest, causing an unsatisfactory construction with the desired targets lost in the interference sidelobes. This thesis investigates ways to mitigate this effect via different signal processing methods. Matlab simulated scenarios are used to illustrate the problem and solutions. Further, this thesis investigates the lateral and range resolution of the back projection, interferometric imaging and self-correlation back projection method. The results are validated by simulation of imaging scenarios through CST and Matlab.

Committee: Robert Burkholder (Advisor); Fernando Teixeira (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2017, Electrical and Computer Engineering

It is of importance to understand the physics as electromagnetic (EM) waves propagate through stratified media, are scattered back from buried irregularities, and are received by an antenna in the near field. To generate better images, we need to incorporate the physics of the phenomena into the imaging algorithm, such as multiple reflections, refractions resulting from the existence of interfaces, and diffractions from embedded targets. A forward model is developed based on the spectral Green's function associated with layered media weighted by the antenna gain pattern, satisfying the near-field condition and incorporating all refraction effects. Thereby, the weak scattering from deeper layers and wide angles will be compensated in a model-based imaging algorithm with the consideration of the refraction coefficients and gain pattern, respectively. To form real-time continuous images of targets embedded in a layered structure, a near-field uniform diffraction tomographic (UDT) imaging algorithm is developed. Conventional diffraction tomography (DT) improperly applies the stationary phase method for stratified environments to evaluate the innermost spectral integral. In DT the large argument is assumed to be the depth, which is not appropriate for near-field imaging. This results in amplitude discontinuities occurring at the interfaces between adjacent layers. The correct dimensionless large argument is the product of the free space wavenumber and the depth, as used in high-frequency asymptotic solutions. UDT therefore yields uniformly continuous images across the interfaces. And like DT, UDT retains the fast Fourier transform (FFT) relation in the algorithm for generating images very efficiently. Both 2D and 3D cases are investigated to verify the efficacy of the proposed UDT algorithm. To overcome the singularity problem caused by nulls in the antenna gain pattern in DT and UDT, a fast back-projection (FBP) imaging algorithm is propose to provide balanced monosta (open full item for complete abstract)

Committee: Robert Burkholder Dr. (Committee Member); Fernando Teixeira Dr. (Committee Member); Graeme Smith Dr. (Committee Member) Subjects: Electrical Engineering; Electromagnetics

Doctor of Philosophy (Ph.D.), University of Dayton, 2016, 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 s (open full item for complete abstract)

Committee: Michael Wicks (Advisor); Keigo Hirakawa (Committee Member); John Loomis (Committee Member); Lorenzo Lo Monte (Committee Member) Subjects: Electrical Engineering