Filtering and Sensor Augmentation for GPS Measurement Reduction in Wildlife Tags

Maxwell Lichtenstein and Gabriel Hugh Elkaim

Abstract:	Animal-mounted GPS-based location tracking has become a core tool for wildlife ecologists. However, the lifetimes of animal mounted devices (or “tags”) are typically limited by battery life, and GPS tracking occupies a large portion of their energy budgets. In this paper, we propose and test several Kalman filter-based algorithms that reduce the GPS duty cycle while still maintaining a threshold of tracking accuracy. These algorithms leverage low-power accelerometry measurements to estimate the uncertainty in the tag’s location, then schedule GPS measurements to suppress that uncertainty. We show that these strategies can reduce average GPS uptime, though at the cost of fidelity in some cases.
Published in:	Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019) September 16 - 20, 2019 Hyatt Regency Miami Miami, Florida
Pages:	1356 - 1363
Cite this article:	Lichtenstein, Maxwell, Elkaim, Gabriel Hugh, "Filtering and Sensor Augmentation for GPS Measurement Reduction in Wildlife Tags," Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019), Miami, Florida, September 2019, pp. 1356-1363. https://doi.org/10.33012/2019.16875
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