دورية أكاديمية

Use of GNSS Doppler for Prediction in Kalman Filtering for Smartphone Positioning ...

التفاصيل البيبلوغرافية
العنوان: Use of GNSS Doppler for Prediction in Kalman Filtering for Smartphone Positioning ...
المؤلفون: Agarwal, Naman, O'Keefe, Kyle
بيانات النشر: IEEE Journal of Indoor and Seamless Positioning and Navigation
سنة النشر: 2023
المجموعة: DataCite Metadata Store (German National Library of Science and Technology)
الوصف: This 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. ...
نوع الوثيقة: text
article in journal/newspaper
اللغة: English
DOI: 10.11575/prism/42587
الإتاحة: https://doi.org/10.11575/prism/42587Test
https://prism.ucalgary.ca/handle/1880/117744Test
حقوق: Creative Commons Attribution 4.0 International ; Attribution 4.0 International ; Unless 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. ; https://creativecommons.org/licenses/by/4.0/legalcodeTest ; cc-by-4.0
رقم الانضمام: edsbas.B714F031
قاعدة البيانات: BASE