Low-Latency, Cloud-Based Positioning for Mobile Applications

Landon Urquhart, Rodrigo Leandro, Sunil Bisnath

Peer Reviewed

Abstract:	Cloud-based GNSS positioning opportunities continue to grow given the relatively low-cost and ease-of-use of modern cloud infrastructure. In the past, cloud-based solutions primarily focused on low power/infrequent update rate solutions to extend battery life of devices. In recent years, with the increase of high precision GNSS solutions on low-cost chipsets, several studies have applied cloud-based techniques to high precision positioning. For cloud-based GNSS processing it is common to divide the logical processing blocks of a GNSS receiver, namely, signal capture, signal processing and position estimation, into various configurations both on-board and external the GNSS sensor itself. This paper focuses primarily on the position estimation component. One of the main challenges for real-time cloud-based navigation is the solution latency (i.e., the time for position updates to be computed and relayed to the remote platform). Given that network latencies are uncertain, due to the dependence on location and environment, this situation poses a significant limitation for general applications and is a major obstacle to safety critical applications that rely on real-time position updates. This paper presents a parallel filter architecture containing two components: 1) a cloud-based position engine for point positioning and 2) a low-latency relative positioning filter for on-board, low-latency position updates. The filter is evaluated using two smartphone datasets made available through the Google Smartphone Decimeter Challenge. Secondly, efficient data communication strategies are critical for low-cost devices as they can be a significant cost to users and product developers. Three data communication strategies are compared to assess the total bandwidth required for data communication for cloud processing compared to traditional RTK services. Data reductions on the range of 26-40% are achieved using two strategies for cloud-based positioning. In addition, various challenges and opportunities of the cloud-based architecture are discussed.
Published in:	Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025) September 8 - 12, 2025 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	2498 - 2512
Cite this article:	Urquhart, Landon, Leandro, Rodrigo, Bisnath, Sunil, "Low-Latency, Cloud-Based Positioning for Mobile Applications," Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 2498-2512. https://doi.org/10.33012/2025.20336
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