Global Navigation Satellite Systems augmentation for mobile devices

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In developing location-based services (LBS) for mobile devices, e.g., augmented reality (AR) software**applications, Shapetrace Inc. has found that user realism is limited by mobile-device-based GPS positioning**inaccuracy and imprecision. Improving positioning performance will allow Shapetrace's simultaneous location**and mapping (SLAM) algorithms and robustly bond location to image recognition features for a more realistic**outdoor AR experience. However, there is no stand-alone, centimetre-to-decimetre-level mobile device**positioning capability in the marketplace. In order to achieve such high performance, existing commercial**solutions require the use of expensive GNSS receivers and antennas, and costly local correction infrastructure.**This project aims to apply a GNSS measurement processing engine (a methodology and software) developed**by the GNSS Laboratory at York University for high-performance positioning and navigation to provide a**solution for this commercial requirement of accurate satellite-based positioning for mobile devices. Elements**of the engine will be used to design high-accuracy positioning processing architectures within the Shapetrace**cloud development, and to perform feasibility studies for various levels of accuracy with selected mobile**devices in urban environments. Solutions will be designed to produce real-time, m-level horizontal (2 sigma)**and cm-level 3D positioning (1 sigma) in urban canyons.**It is expected that the high-performance positioning capability will be commercialized for Shapetrace clients**through its cloud server. This capability will provide a competitive differentiator that is expected to increase**Shapetrace revenue through sales of its existing app services, and through the company's ability to provide**significantly more and varied AR experiences and precise LBS to many new clients.