High Precision Water Level Detection for a Reservoir Using CLAS and Adaptive Filter

Mao Konishi, Norizumi Motooka, Yuki Sato

Peer Reviewed

Abstract:	An application of Centimeter-Level Augmentation Service (CLAS) to detecting changes in water level of reservoirs with high precision using adaptive filtering is presented. One method to estimate the water level is by floating and locating a buoy in the reservoir using on-board GNSS measurements. In such scenario, the positioning algorithm is expected to be both stable, under regular conditions, and highly responsive, whenever the water level changes. To achieve this, a method to adaptively determine appropriate process noise by residual feedback is integrated into the PPP-RTK algorithm. The proposed method was tested under two settings: an on-ground test, and an on-site test at a reservoir. In both tests, the positioning results showed significantly small fluctuations under stable conditions, while tracking large and small height changes in a timely manner. The system achieved positioning accuracy well under those defined in CLAS’s performance standards over the month of on-site test.
Published in:	Proceedings of the 2022 International Technical Meeting of The Institute of Navigation January 25 - 27, 2022 Hyatt Regency Long Beach Long Beach, California
Pages:	812 - 818
Cite this article:	Konishi, Mao, Motooka, Norizumi, Sato, Yuki, "High Precision Water Level Detection for a Reservoir Using CLAS and Adaptive Filter," Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, Long Beach, California, January 2022, pp. 812-818. https://doi.org/10.33012/2022.18182
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