Vision based Navigation: Enhancing GPS Coordinate Accuracy in Urban Environments Using High-Resolution Ortho Photos and 3D City Models
In urban environments, GPS-based positioning systems face significant challenges, including signal blockages, low satellite visibility, disconnections, and so caused mainly by dense building structures and urban canyons. This research aims to overcome these limitations by leveraging accurate 3-centimeter resolution ortho photos and detailed 3D city models as auxiliary data sources for enhancing GPS measurement accuracy.
The proposed study will focus on integrating high-resolution spatial data with GPS measurements to develop a robust positioning framework. The research will involve designing algorithms to align GPS data with orthophotos and 3D models to correct positioning errors, predict locations during GPS signal loss, and provide high-precision geolocation in urban settings. By testing the system in real-world urban scenarios, this thesis will evaluate the effectiveness of the approach in mitigating GPS limitations and improving location-based services.
This research will investigate the possibility of using high-resolution geospatial data available in the Netherlands to improve the accuracy of GPS-based observations in urban environments. In recent years, the resolution and accuracy of available data have significantly advanced, with the industry now publishing ortho photos and 3D models of urban regions at an impressive resolution and accuracy of 3 centimeters. These developments present new opportunities for enhancing location-based services.
However, many projects face challenges when relying on GPS in dense urban areas, where GPS signals can become unreliable or lost due to obstructions. This research seeks to address these limitations by exploring the applicability of using high-resolution ortho photos and 3D city models to enhance the location accuracy provided by GPS or to bridge gaps in positioning when GPS is disconnected. By employing image matching techniques with the available datasets, the study aims to establish a reliable method for maintaining precise localization in challenging urban environments.
This work will answer critical questions, such as how to effectively integrate available aerial imagery and historical geospatial data into a GPS-aided system and what level of accuracy can realistically be achieved through such integration. The research will employ a multidisciplinary approach, combining photogrammetry, image processing, and navigation expertise. Conducted in close collaboration with industry, the study will ensure practical relevance and applicability, leveraging cutting-edge data and technologies to deliver innovative solutions for urban navigation challenges.
P.S. The image is AI-generated
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