Open AccessEnhance accuracy of kinematic GPS positioning with Kalman filtering
Author(s) -
Vinh Đinh Xuân
Publication year - 2018
Publication title -
tạp chí khoa học đại học quốc gia hà nội: nghiên cứu giáo dục (vnu journal of science: education research)/tạp chí khoa học đại học quốc gia hà nội: các khoa học trái đất và môi trường (vnu journal of science: earth and environmental sciences)
Language(s) - English
Resource type - Journals
eISSN - 2615-9279
pISSN - 2588-1094
DOI - 10.25073/2588-1094/vnuees.4241
Subject(s) - kalman filter , global positioning system , gps/ins , control theory (sociology) , computer science , position (finance) , extended kalman filter , kinematics , differential gps , assisted gps , artificial intelligence , telecommunications , physics , classical mechanics , control (management) , finance , economics
The article discusses the Kalman filter application for temporal random motion of the GPS receiver location. The motion of the GPS receiver is a space state model with time-varying. The spatial state model is usually represented by linear differential equations with white noise. When the state of space fluctuates over time, it is represented by Riccati equations, ie nonlinear differential equations.Kalman filter for optimal estimation reliable, even unstable system, respectively random moves of the GPS receiver. The mobile GPS coordinates over time are compared to the coordinates in a previous static test, confirming that the Kalman filter can apply an optimal estimate of the mobile GPS position. This reduces the investment cost and increases the efficiency of using a common GPS receiver.