Implementing a Sensor Fusion Algorithm for 3D Orientation Detection with Inertial/Magnetic Sensors

  • Fatemeh AbyarjooEmail author
  • Armando Barreto
  • Jonathan Cofino
  • Francisco R. Ortega
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 313)


In this paper a sensor fusion algorithm is developed and implemented for detecting orientation in three dimensions. Tri-axis MEMS inertial sensors and tri-axis magnetometer outputs are used as input to the fusion system. A Kalman filter is designed to compensate the inertial sensors errors by combining accelerometer and gyroscope data. A tilt compensation unit is designed to calculate the heading of the system.


Sensors 3D Detection Algorithms filters 



This work was sponsored in part by NFS grants HRD-0833093, and CNS-0959985.


  1. 1.
    Ji-Hwan Kim, 3-D Hand Motion Tracking and Gesture Recognition Using a Data Glove, IEEE International Symposium on Industrial Electronics, Seol, Korea, 2009Google Scholar
  2. 2.
    Clare Chen, Grace Li, Peter Ngo, Connie Sun, Motion Sensing Technology, Management of Technology – E 103, 2011Google Scholar
  3. 3.
    C.Verplaetes, Inertial Proprioceptive devices: Self-motion-sensing toys and tools, IBM SYSTEMS JOURNAL, VOL 35, NOS 3&4, 1996Google Scholar
  4. 4.
    I-K. Park, J-H. Kim, H-S. Hong, An Implementation of an FPGA-Based Embedded Gesture Recognizer Using a Data Glove, Conference On Ubiquitous Information Management And Communication Processing of the 2nd international conference on Ubiquitous information management and communication 2008, Suwon,Korea, January 31 - February 01, 2008, pp.496-500Google Scholar
  5. 5.
    Fg A. M. Khan, T-S. Kim, Accelerometer Signal-Based Human Activity Recognition using Augmented Autoregressive Model Coefficients and Artificial Neural Nets, " IEEE EMBC 2008, pp. 5172-5175.Google Scholar
  6. 6.
    Oliver J.Woodman, An Introduction to Inertial Navigation”, Technical Report, University of Cambridge, 2007Google Scholar
  7. 7.
    Walid Abdel-Hamid, Accuracy Enhancement of Integrated MEMS-IMU/GPS Systems for Land Vehicular Navigation Applications, University of CAGARY, January 2005Google Scholar
  8. 8.
    Thilakshan Kanesalingam, Motion Tracking Glove for Human-Machine Interaction: Inertial Guidance, Mc Master University, Hamilton, Ontario, CanadaGoogle Scholar
  9. 9.
    Doug Vargha, Motion Processing Technology Driving New Innovations in Consumer Products, InvensenseGoogle Scholar
  10. 10.
    Phil Kim, Kalman Filter for Beginners with Matlab Examples”, CreateSpace Independent Publishing Platform, 2011Google Scholar
  11. 11.
    Seong Yun, Chan Gook Park, A Calibration Technique for a Two-Axis Magnetic Compass in Telematics Devices, ETRI Journal, Volume 27, Number 3, June 2005Google Scholar
  12. 12.
    M.J. Caruso, Application of Magnetometer Sensors in Navigation Systems, Sensors and Actuators, SAE SP-1220, Feb. 1997, pp. 15-21Google Scholar
  13. 13.
    Adam N.Bingaman, Tilt-Compensated Magnetic Field Sensor, Master Dissertation, Virginia Polytechnic Institute and State University, May 2010Google Scholar
  14. 14.
    H.J. Luinge, P.H. Veltik, Measuring orientation of human body segments using miniature gyroscopes and accelerometer, Medical & Biological Engineering & Computing 2005, Vol.43Google Scholar
  15. 15.
    Rong Zhu, Zhaoying Zhou, A Real-Time Articulated Human Motion Tracking Using Tri-Axis Inertial/Magnetic Sensors Package, IEEE TRANSACTION ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL.12, NO. 2, JUNE 2004Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Fatemeh Abyarjoo
    • 1
    Email author
  • Armando Barreto
    • 1
  • Jonathan Cofino
    • 1
  • Francisco R. Ortega
    • 2
  1. 1.Electrical and Computer Engineering DepartmentFlorida International UniversityMiamiUSA
  2. 2.School of Computing and Information ScienceFlorida International UniversityMiamiUSA

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