Agarwal, NamanO'Keefe, Kyle2024-01-032024-01-032023-11-28Agarwal, N., & O’Keefe, K. (2023). Use of GNSS Doppler for Prediction in Kalman Filtering for Smartphone Positioning. IEEE Journal of Indoor and Seamless Positioning and Navigation, 1, 151–160. https://doi.org/10.1109/JISPIN.2023.3337188https://hdl.handle.net/1880/11774410.11575/PRISM/42587This article demonstrates an alternative approach that uses global navigation satellite system (GNSS) Doppler measurements in a Kalman filter (KF) to improve the accuracy of GNSS smartphone positioning. The proposed method automates the process of estimating the uncertainty of the dynamics model of the system, which is still a challenge for the conventional KF-based GNSS positioning methods that require heuristic tuning. Automation of dynamics model uncertainty estimation also demonstrates notable improvement in GNSS outlier detection or fault detection and exclusion. In addition, this article will perform a quality assessment of the GNSS observations obtained from two Android smartphones and investigate the performance of the proposed method when using GPS L1 + Galileo E1 signals compared to GPS L5 + Galileo E5a signals.enUnless otherwise indicated, this material is protected by copyright and has been made available with authorization from the copyright owner. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/Article495568-201710.1109/JISPIN.2023.3337188