Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-23T19:45:04.040Z Has data issue: false hasContentIssue false
  • English
  • Français

Heuristic Drift Elimination for Personnel Tracking Systems

Published online by Cambridge University Press:  13 September 2010

Johann Borenstein  and
Lauro Ojeda
Johann Borenstein*
Affiliation:
(The University of Michigan)
Lauro Ojeda
Affiliation:
(The University of Michigan)
*
(Email: johannb@umich.edu)
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper pertains to the reduction of the effects of measurement errors in rate gyros used for tracking, recording, or monitoring the position of persons walking indoors. In such applications, bias drift and other gyro errors can degrade accuracy within minutes. To overcome this problem we developed the Heuristic Drift Elimination (HDE) method, that effectively corrects bias drift and other slow-changing errors. HDE works by making assumptions about walking in structured, indoor environments. The paper explains the heuristic assumptions and the HDE method, and shows experimental results. In typical applications, HDE maintains near-zero heading errors in walks of unlimited duration.

Keywords

Personnel trackingPersonal locatorGyroDrift
Type
Research Article
Information
The Journal of Navigation , Volume 63 , Issue 4 , October 2010 , pp. 591 - 606
Copyright
Copyright © The Royal Institute of Navigation 2010

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

Basnayake, C., Mezentsev, O., Lachapelle, G., and Cannon, M. E. (2005). An HSGPS, inertial and map-matching integrated portable vehicular navigation system for uninterrupted real-time vehicular navigation. International Journal of Vehicle Information and Communication Systems, 1, 131–151.CrossRefGoogle Scholar
Borenstein, J, Ojeda, L., and Kwanmuang, S. (2009). Heuristic Reduction of Gyro Drift in a Personal Dead-reckoning System. The Journal of Navigation, 62, 41–58.CrossRefGoogle Scholar
Cavallo, F.Sabatini, A. M., and Genovese, V. (2005). A step toward GPS/INS personal navigation systems: real-time assessment of gait by foot inertial sensing. IEEE/RSJ International Conference on Intelligent Robots and Systems.Google Scholar
Chen, X. (2004). Modeling Temperature Drift of FOG by Improved BP Algorithm and by Gauss-Newton Algorithm. Lecture Notes in Computer Science – Springer Berlin/Heidelberg, ISBN 978-3-540-22843-1.CrossRefGoogle Scholar
Cho, S. Y.Lee, K. W.Park, C. G., and Lee, J. G. (2003). A Personal Navigation System Using Low-Cost MEMS/GPS/Fluxgate. Proceedings of the 59th Institute of Navigation (ION) Annual Meeting, Albuquerque, NM.Google Scholar
Grejner-Brzezinska, D. A., et al. (2006). Multi-sensor personal navigator supported by human motion dynamics model. 3rd IAG/12th FIG Symposium, Baden, Austria.Google Scholar
Ferre-Pikal, E. S. et al. (1997). Draft revision of IEEE STD 1139-1988 standard definitions of physical quantities for fundamental, frequency and time metrology-random instabilities. Proceedings of the 1997 IEEE Frequency Control Symposium, 1997, Orlando, FL, USA.CrossRefGoogle Scholar
MemSense, LLC, http://www.memsense.com, Rapid City, SD, USA.Google Scholar
Mohinder, S. et al. (2002). Global Positioning Systems, Inertial Navigation, and Integration. Copyright 2001 John Wiley & Sons, Inc.Google Scholar
Ojeda, L. and Borenstein, J. (2007a). Non-GPS Navigation with the Personal Dead-reckoning System. Proceedings of the SPIE Defense and Security Conference, Unmanned Systems Technology IX, Orlando, Florida.CrossRefGoogle Scholar
Ojeda, L. and Borenstein, J. (2007b). Non-GPS Navigation for Security Personnel and Emergency Responders. The Journal of Navigation, 60, 391–407.CrossRefGoogle Scholar
Yun, X., Bachmann, E. R., Moore, H. IV, and Calusdian, J. (2007). Self-contained Position Tracking of Human Movement Using Small Inertial/Magnetic Sensor Modules. 2007 IEEE International Conference on Robotics and Automation, Rome, ItalyCrossRefGoogle Scholar