Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/30220
Title: | Advanced Real-time Image Reconstruction Algorithms for Microwave and Millimeter-wave Imaging |
Authors: | Kazemivala, Romina |
Advisor: | Nikolova, Natalia Koleva |
Department: | Electrical and Computer Engineering |
Publication Date: | 2024 |
Abstract: | Microwave/millimeter-wave imaging technology, distinguished by its ability to detect and visualize objects obscured by non-transparent materials, finds diverse applications in fields such as security, medical diagnostics, and industrial nondestructive testing. These applications often require rapid, accurate imaging capabilities that can operate effectively even in non-ideal conditions. This work's principal contribution is the advanced applications of Fourier-space scattered power mapping (F-SPM), which facilitates significant improvements in image reconstruction quality. Firstly, we introduce a novel integration of F-SPM with dual simultaneous utilization of the Born and Rytov approximations. This synergy enhances both the structural and quantitative accuracy of the imaging results by leveraging the unique strengths of each approximation. Secondly, we adapted Fourier-space scattered power mapping (F-SPM) for time-domain data, achieving the same performance as the original frequency-domain method. Simulation and experimental validations are conducted along with the concept of linear frequency-modulated radar (LFM), with performance compared to the rapid microwave holography method. Additionally, we present a broader application of the F-SPM method, which processes data from randomly placed spatial positions. This approach allows for real-time image updates concurrent with ongoing measurements, progressively refining and converging in quality as additional data is acquired. The innovative applications of F-SPM demonstrated in this study enable the achievement of high-quality images with fewer samples than typically required by the Nyquist criterion. |
URI: | http://hdl.handle.net/11375/30220 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Kazemivala_Romina_2024August_PhD.pdf | 33.66 MB | Adobe PDF | View/Open |
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