First Place Award Winner of the Smartphone Decimeter Challenge: Global Optimization of Position and Velocity by Factor Graph Optimization

Taro Suzuki

Abstract:	This paper describes the first-place solution at a Google smartphone decimeter challenge (GSDC), which was held from May to August 2021. The GSDC is a competition for positioning accuracy using raw global navigation satellite system (GNSS) data from smartphones. GNSS data from smartphones have lower signal levels and higher noise in GNSS observations compared to commercial GNSS receivers. This makes it difficult to directly apply existing high-precision positioning methods such as precise point positioning and real-time kinematic GNSS. In this paper, we develop a method to estimate the position of a smartphone with high accuracy in the framework of factor graph optimization (FGO) using the accumulated delta range (ADR) observed from the smartphone. The use of ADR enables highly accurate relative positions to be estimated, and highly accurate absolute positions are estimated by using pseudorange observations corrected using GNSS reference stations as constraints for FGO. Using the proposed method, we estimated the location of the smartphone and tackled the competition. The final public score was 2.86 m, and the rank was 2nd. The final private score was 1.62 m, which was first place.
Published in:	Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021) September 20 - 24, 2021 Union Station Hotel St. Louis, Missouri
Pages:	2974 - 2985
Cite this article:	Suzuki, Taro, "First Place Award Winner of the Smartphone Decimeter Challenge: Global Optimization of Position and Velocity by Factor Graph Optimization," Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, pp. 2974-2985. https://doi.org/10.33012/2021.18109
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