Hostname: page-component-77c89778f8-vsgnj Total loading time: 0 Render date: 2024-07-17T11:59:37.418Z Has data issue: false hasContentIssue false
  • English
  • Français

Implementation and Performance Assessment of a Vector Tracking Method Based on a Software GPS Receiver

Published online by Cambridge University Press:  14 October 2011

Sihao Zhao ,
Mingquan Lu  and
Zhenming Feng
Sihao Zhao*
Affiliation:
(Dept. of Electronic Engineering, Tsinghua University, Beijing, China)
Mingquan Lu
Affiliation:
(Dept. of Electronic Engineering, Tsinghua University, Beijing, China)
Zhenming Feng
Affiliation:
(Dept. of Electronic Engineering, Tsinghua University, Beijing, China)
*
(Email: zsh@mails.thu.edu.cn)
Get access Rights & Permissions [Opens in a new window]

Abstract

A number of methods have been developed to enhance the robustness of Global Positioning System (GPS) receivers when there are a limited number of visible satellites. Vector tracking is one of them. It utilizes information from all channels to aid the processing of individual channels to generate receiver positions and velocities. This paper analyzes relationships among code phase, carrier frequency, and receiver position and velocity, and presents a vector loop-tracking algorithm using an Extended Kalman filter implemented in a Matlab-based GPS software receiver. Simulated GPS signals are generated to test the proposed vector tracking method. The results show that when some of the satellites are blocked, the vector tracking loop provides better carrier frequency tracking results for the blocked signals and produces more accurate navigation solutions compared with traditional scalar tracking loops.

Keywords

GPS software receiverVector trackingKalman filter
Type
Research Article
Information
The Journal of Navigation , Volume 64 , Supplement S1: Chinese Beidou and the Next Generation GNSS , November 2011 , pp. S151 - S161
Copyright
Copyright © The Royal Institute of Navigation 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Borre, K., Akos, D., Bertelsen, N., Rinder, P. and Jensen, S. H. (2007). A Software-Defined GPS and Galileo Receiver: A Single-Frequency Approach. Springer, New York.Google Scholar
Kaplan, E. D. and Hegarty, C. (2006). Understanding GPS: Principles and Applications, 2nd Ed, Artech House Inc, MA.Google Scholar
Lashley, M. (2009). Modeling and Performance Analysis of GPS Vector Tracking Algorithms. PhD Dissertation, Auburn University, Alabama.Google Scholar
Parkinson, B. W. and Spilker, J. J. (1996). Global Positioning System: Theory and Applications. American Institute of Aeronautics and Astronautics, Washington DC.CrossRefGoogle Scholar
Pany, T., Kaniuth, R. and Eissfeller, B. (2005). Deep integration of navigation solution and signal processing. Proceedings of Institute of Navigation GPS/GNSS Conference, Long Beach, CA.Google Scholar
Petovello, M. and Lachapelle, G. (2006). Comparison of Vector-based Software Receiver Implementations with Application to Ultra-tight GPS/INS Integration. Proceedings of Institute of Navigation GPS/GNSS Conference, Fort Worth, TX.Google Scholar
Qin, Y., Zhang, H. and Wang, S. (1998). Kalman Filter and Principles of Integrated Navigation. Northwestern Polytechnical University Press, Xi'an, Shaanxi Province, China. (In Chinese)Google Scholar
Zhao, S. and Akos, D. (2011). An Open Source GPS/GNSS Vector Tracking Loop – Implementation, Filter Tuning, and Results. Proceedings of Institute of Navigation International Technical Meeting, San Diego, CA.Google Scholar
Zhu, Z., Tang, G., Cheng, Z. and Huangfu, K. (2009). GPS Signal Tracking Algorithm Based-on Vector Delay Locked Loop. Progress in Natural Science, 19(9). (In Chinese)Google Scholar