Date of Award
2025
Document Type
Open Access Dissertation
Degree Name
Doctor of Philosophy in Electrical Engineering (PhD)
Administrative Home Department
Department of Electrical and Computer Engineering
Advisor 1
Durdu Guney
Advisor 2
Radwin Askari
Committee Member 1
Greg P. Waite
Committee Member 2
Zhaohui Wang
Abstract
Imaging through noisy media is inherently challenging, particularly when the noise stems from dynamic and stochastic environments such as atmospheric turbulence. However, these noisy media are not merely obstacles. If imaging can be achieved effectively under such conditions, it opens the door to transformative applications in remote sensing and free-space optical communication. One domain where this potential is especially critical is the remote sensing of seismic and geophysical activity. Traditional approaches rely on in situ sensors that are often difficult or dangerous to deploy in volatile or inaccessible terrains, such as active volcanic regions. Atmospheric turbulence further complicates long-distance optical imaging, introducing phase and amplitude distortions that degrade measurement fidelity. This dissertation presents a novel Moiré-based remote sensing framework, enhanced with Active Convolved Illumination (ACI) and deep learning techniques, to overcome the challenges posed by atmospheric turbulence in optical propagation. ACI is an optical method that actively mitigates turbulence-induced distortions. When combined with learning-based post-processing, this approach enables high-resolution imaging in remote sensing scenarios. The Moiré-based apparatus, designed specifically for remote ground motion measurement, leverages these techniques to achieve high-fidelity displacement detection over long distances, without the need for physical contact or on-site instrumentation. The proposed methodology provides a robust, scalable, and non-invasive solution for geophysical monitoring in complex and hazardous environments, significantly advancing the capabilities of optical remote sensing under turbulent atmospheric conditions.
Recommended Citation
Moazzam, Adrian Ali, "ENHANCED MOIRÉ TECHNIQUE FOR REMOTE SENSING OF GROUND MOTION INTEGRATING ACTIVE CONVOLVED ILLUMINATION AND DEEP LEARNING", Open Access Dissertation, Michigan Technological University, 2025.