Open AccessPositioning accuracy improvement in high‐speed GPS receivers using sequential extended Kalman filter
Author(s) -
Rahemi Narges,
Mosavi Mohammad Reza
Publication year - 2021
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/sil2.12027
Subject(s) - global positioning system , kalman filter , computer science , noise (video) , filter (signal processing) , process (computing) , covariance matrix , assisted gps , algorithm , control theory (sociology) , real time computing , artificial intelligence , computer vision , telecommunications , image (mathematics) , control (management) , operating system
It is well known that in high‐speed movements, the positioning accuracy of global positioning system (GPS) receivers decreases drastically. The models presented so far to describe high‐speed motion do not represent the state of the system precisely, so positioning accuracy with the methods based on these models is not appropriate. Here, a comprehensive method is proposed to solve the accuracy issue of the single‐frequency GPS receiver at high‐speed motions without increasing the computational complexity. Suitable modelling of the GPS receivers at high‐speed motion, using the sequential extended Kalman filter, correct determination of the process noise covariance matrix and accurately estimating the variance of the observations are the basics of the proposed approach. Simulations with different data and motion scenarios (at speeds from 100 to 7300 m/s) show that the proposed method, while not increasing the computational cost, improves the accuracy of positioning more than 70% when compared to the conventional methods.