Global Navigation Satellite Systems augmentation for mobile devices

在为移动设备开发基于位置的服务（LBS）时，例如增强现实（AR）软件应用程序，Shapetrace Inc.发现基于移动设备的GPS定位不准确和不精确限制了用户的真实感。改进定位性能将允许Shapetrace的同步定位和映射（SLAM）算法，并将位置与图像识别功能稳健地结合在一起，以实现更逼真的户外AR体验。然而，目前市场上还没有独立的厘米到厘米级别的移动设备定位能力。为了实现如此高性能，现有的商业解决方案需要使用昂贵的GNSS接收器和天线，以及昂贵的本地校正基础设施。**本项目旨在应用由约克大学GNSS实验室**开发的用于高性能定位和导航的GNSS测量处理引擎（一种方法和软件），为移动设备精确的卫星定位这一商业需求提供**解决方案。该引擎的元素将用于在Shapetrace**云开发中设计高精度定位处理架构，并在城市环境中使用选定的移动设备进行各种精度水平的可行性研究。将设计解决方案，在城市峡谷中产生实时的m级水平（2西格玛）**和cm级3D定位（1西格玛）。**预计Shapetrace客户端将通过其云服务器实现高性能定位能力的商业化**。这种能力将提供差异化的竞争优势，通过销售其现有的应用服务，并通过公司为许多新客户提供更多和更多样化的AR体验和精确的LBS的能力，有望增加Shapetrace的收入。

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.