Dinh Xuan Vinh

Main Article Content

Abstract

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. We proposed extending the Kalman filter with parameters suitable for the measurement conditions established large scale maps in Vietnam today.Coordinate points of GPS mobile over time is compared with coordinate values in a case of static measurements previously with high precision, confirming the Kalman filter extended with parameters suitable to estimate the optimal mobile GPS receiver location. This reduces the investment cost and increases the efficiency of using a common GPS receiver.


Key words: Kalman filter, kinematic GPS.

Keywords: Kalman filter, kinematic GPS.

References

[1] R.E. Kalman, A New Approach to Linear Filtering and Prediction Problems, Journal of Basic Engineering, 82 (series D):34-45. Copyright @ 1960 by ASME.1960.
[2] Phan Văn Hiến, Đinh Xuân Vinh, Ứng dụng lọc Kalman trong phân tích biến dạng nhà cao tầng do bức xạ nhiệt mặt trời. Tạp chí Xây dựng, số 5-2010. ISSN 0866-0762.2010.
[3] Grewal, Mohinder S, Angus P. Andrews. Kalman filtering : theory and practice using MATLAB. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. ISBN 978-0-470-17366-4 (cloth)2008.
[4] Đinh Xuân Vinh, Phan Văn Hiến, Nguyễn Bá Dũng, Lý thuyết và phương pháp phân tích biến dạng. Nhà xuất bản Tài nguyên Môi trường và Bản đồ Việt Nam. ISBN: 978-604-904-875-3.2016.
[5] Arthur Gelb, Joseph F. Kasper, Raymond A. Nash, Charles F. Price, Arthur A. Sutherland. Applied Optimal Estimation. Technical Staff the Analytic Sciences Corporation. THE M.I.T. PRESS. Massachusetts Institute of Technology.
[6] Daniel Zwillinger. CRC Standard Mathematical Tables and Formulae. CRC Press. 2003.
[7] Alfred Leick. GPS Satellite Surveying. John Wiley & Sons, Inc. All rights reserved. ISBN 0-471-05930-7 (cloth).2004.
[8] Tomoji TAKASU. “RTKLIB: Open Source Program Package for RTK-GPS”. Tokyo University of Marine Science and Technology. 2009.
[9] Norman Morrison, Intro to Sequential Smoothing and Prediction. McGraw-Hil Book Company, New York. 1969.
[10] Heiner Kuhlmann, “Kalman – filtering with coloured measurement noise for deformation analysis”, Proceedings, 11th FIG Symposium on Deformation Measurements, Santorini, Greece, 2003.