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201351 https://hdl.handle.net/2286/R.2.N.201351 http://rightsstatements.org/vocab/InC/1.0/ http://creativecommons.org/licenses/by-nc-sa/4.0 2025-05 29 pages Colyar, Adam Chavez, Maria Baillot, Yohan Barrett, The Honors College Computer Science and Engineering Program Accurate drone localization in urban environments remains a challenge due to GPS signal blockage, multipath interference, and unreliable vertical positioning caused by dense architectural structures. This research investigates an alternative approach using Immersal’s visual positioning system (VPS) to enable image-based localization without relying on simultaneous localization and mapping (SLAM) or ARFoundation for mobile devices. By adapting the Immersal pipeline to accept external camera input, this work simulates a drone-based setup using webcam footage and estimates focal parameters to support localization. While real drone deployment is outside the project scope, the resulting software provides a foundation for future integration with drone hardware by identifying the necessary sensor data for visual localization and connecting the necessary pipeline data. This approach lays the groundwork for infrastructure-free navigation in GPS-degraded urban environments, and the system has successfully demonstrated the ability to generate maps and extract camera poses using custom captured images run through Immersal. This was validated through webcam-based tests and offline drone footage, where Immersal returned consistent pose estimates and successfully built .ply-format spatial maps using synchronized image-pose data. Visual Positioning System Drone Localization Immersal Unity GPS Mapping Simulation Software Augmenting Drone GPS Precision Using Immersal’s Visual Positioning System