abstract: The objective of this work is to design a novel method for imaging targets and scenes which are not directly visible to the observer. The unique scattering properties of terahertz (THz) waves can turn most building surfaces into mirrors, thus allowing someone to see around corners and various occlusions. In the visible regime, most surfaces are very rough compared to the wavelength. As a result, the spatial coherency of reflected signals is lost, and the geometry of the objects where the light bounced on cannot be retrieved. Interestingly, the roughness of most surfaces is comparable to the wavelengths at lower frequencies (100 GHz – 10 THz) without significantly disturbing the wavefront of the scattered signals, behaving approximately as mirrors. Additionally, this electrically small roughness is beneficial because it can be used by the THz imaging system to locate the pose (location and orientation) of the mirror surfaces, thus enabling the reconstruction of both line-of-sight (LoS) and non-line-of-sight (NLoS) objects.
Back-propagation imaging methods are modified to reconstruct the image of the 2-D scenario (range, cross-range). The reflected signal from the target is collected using a SAR (Synthetic Aperture Radar) set-up in a lab environment. This imaging technique is verified using both full-wave 3-D numerical analysis models and lab experiments.
The novel imaging approach of non-line-of-sight-imaging could enable novel applications in rescue and surveillance missions, highly accurate localization methods, and improve channel estimation in mmWave and sub-mmWave wireless communication systems. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2019
| Identifer | oai:union.ndltd.org:asu.edu/item:55514 |
| Date | January 2019 |
| Contributors | Doddalla, Sai Kiran kiran (Author), Trichopoulos, George (Advisor), Alkhateeb, Ahmed (Committee member), Zeinolabedinzadeh, Saeed (Committee member), Aberle, James (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 74 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/ |
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