Conference item
SnapperGPS -- Algorithms for energy-efficient low-cost location estimation using GNSS signal snapshots
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1145/3485730.3485931
Authors
- Publisher:
- Association for Computing Machinery
- Publication date:
- 2021-11-15
- Acceptance date:
- 2021-10-13
- Event title:
- SenSys ’21: ACM Conference on Embedded Networked Sensor Systems
- Event location:
- Coimbra, Portugal
- Event website:
- https://sensys.acm.org/2021/
- Event start date:
- 2021-11-15
- Event end date:
- 2021-11-17
- DOI:
- Language:
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English
- Keywords:
- Pubs id:
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1203264
- Local pid:
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pubs:1203264
- Deposit date:
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2021-10-18
Terms of use
- Copyright holder:
- Beuchert and Rogers.
- Copyright date:
- 2021
- Rights statement:
- © 2021 Copyright held by the owner/author(s).
- Notes:
- This is the accepted manuscript version of the conference paper. The final version is available online from the Association for Computing Machinery at https://doi.org/10.1145/3485730.3485931
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