SnapperGPS: algorithms for energy-efficient low-cost location estimation using GNSS signal snapshots

Beuchert, Jonas and Rogers, Alex 2021. SnapperGPS: algorithms for energy-efficient low-cost location estimation using GNSS signal snapshots. Presented at: SenSys '21: The 19th ACM Conference on Embedded Networked Sensor Systems, Coimbra, Portugal, November 15 - 17 2021. SenSys '21: Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems. New York: Association for Computing Machinery, pp. 165-177. 10.1145/3485730.3485931

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Abstract

Snapshot GNSS is a more energy-efficient approach to location estimation than traditional GNSS positioning methods. This is beneficial for applications with long deployments on battery such as wildlife tracking. However, only a few snapshot GNSS implementations have been presented so far and all have disadvantages. Most significantly, they typically require the GNSS signals to be captured with a certain minimum resolution, which demands complex receiver hardware capable of capturing multi-bit data at sampling rates of 16 MHz and more. By contrast, we develop fast algorithms that reliably estimate locations from twelve-millisecond signals that are sampled at just 4 MHz and quantised with only a single bit per sample. This allows us to build a snapshot receiver at an unmatched low cost of $14, which can acquire one position per hour for a year. On a challenging public dataset with thousands of snapshots from real-world scenarios, our system achieves 97% reliability and 11 m median accuracy, comparable to existing solutions with more complex and expensive hardware and higher energy consumption. We provide an open implementation of the algorithms as well as a public web service for cloud-based location estimation from low-quality GNSS signal snapshots.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Association for Computing Machinery
ISBN:	9781450390972
Last Modified:	06 Dec 2024 10:30
URI:	https://orca.cardiff.ac.uk/id/eprint/173416

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