Table of Contents Author Guidelines Submit a Manuscript
Journal of Sensors
Volume 2016, Article ID 5365983, 16 pages
http://dx.doi.org/10.1155/2016/5365983
Research Article

A New Technique for Integrating MEMS-Based Low-Cost IMU and GPS in Vehicular Navigation

1LASSENA Laboratory, École de Technologie Supérieure, 1100 Notre-Dame Street West, Montreal, QC, Canada H3C 1K3
2Marine Navigation Research Institute, College of Automation, Harbin Engineering University, Harbin 150001, China
3LIV Laboratory, Electrical and Computer Engineering Department, Université de Sherbrooke, Sherbrooke, QC, Canada J1K 2R1

Received 20 November 2015; Revised 4 April 2016; Accepted 28 April 2016

Academic Editor: Maan E. El Najjar

Copyright © 2016 Neda Navidi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. W. Zellner, R. M. van Auken, D. P. Chiang, P. C. Broen, J. Kelly, and Y. Sugimoto, “Extension of the Honda-DRI ‘Safety Impact Methodology’ (SIM) for the NHTSA Advanced Crash Avoidance Technology (ACAT) program and application to a prototype advanced collision mitigation braking system,” SAE International Journal of Passenger Cars—Mechanical Systems, vol. 2, no. 1, pp. 875–894, 2009. View at Publisher · View at Google Scholar · View at Scopus
  2. T. Hai Ta, D. Minh Truong, T. Thanh Thi, H. Nguyen, T. Dinh Nguyen, and G. Belforte, “Multi-GNSS positioning campaign in South-East Asia,” Coordinates, vol. 9, pp. 11–20, 2013. View at Google Scholar
  3. D. M. Truong and T. H. Ta, “Development of real multi-GNSS positioning solutions and performance analyses,” in Proceedings of the International Conference on Advanced Technologies for Communications (ATC '13), pp. 158–163, Ho Chi Minh, Vietnam, October 2013. View at Publisher · View at Google Scholar · View at Scopus
  4. K.-P. Schwarz and N. El-Sheimy, “Future positioning and navigation technologies,” in Study Performed under the Scientific Services Agreement with Batelle, Columbus Division and Topographic Engineering Center, Fort Belvoir, VA, USA, 1999. View at Google Scholar
  5. M. S. Grewal, L. R. Weill, and A. P. Andrews, Global Positioning Systems, Inertial Navigation, and Integration, John Wiley & Sons, New York, NY, USA, 2007.
  6. J. Georgy, U. Iqbal, and A. Noureldin, “Quantitative comparison between kalman filter and particle filter for low cost INS/GPS integration,” in Proceedings of the 6th International Symposium on Mechatronics and its Applications (ISMA '09), pp. 1–7, Sharjah, United Arab Emirates, March 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. A. Oppenheim and R. Schafer, Discrete-Time Signal Processing: Pearson New International Edition, Pearson Education, Upper Saddle River, NJ, USA, 2013.
  8. A. Noureldin, T. B. Karamat, M. D. Eberts, and A. El-Shafie, “Performance enhancement of MEMS-based INS/GPS integration for low-cost navigation applications,” IEEE Transactions on Vehicular Technology, vol. 58, no. 3, pp. 1077–1096, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. T. B. Karamat, Implementation of tightly coupled INS/GPS integration for land vehicle navigation [M.S. thesis], Electrical engineering, Royal Military College of Canada, 2009.
  10. J. Pusa, Strapdown inertial navigation system aiding with nonholonomic constraints using indirect Kalman filtering [M.S. thesis], Department of Mathematics, Tampere University of Technology, 2009.
  11. Z. Shen, J. Georgy, M. J. Korenberg, and A. Noureldin, “Low cost two dimension navigation using an augmented Kalman filter/Fast Orthogonal Search module for the integration of reduced inertial sensor system and Global Positioning System,” Transportation Research Part C: Emerging Technologies, vol. 19, no. 6, pp. 1111–1132, 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. L. Zhao, H. Qiu, and Y. Feng, “Study of robust H filtering application in loosely coupled INS/GPS system,” Mathematical Problems in Engineering, vol. 2014, Article ID 904062, 10 pages, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  13. P. Aggarwal, Z. Syed, and N. El-Sheimy, “Hybrid Extended Particle Filter (HEPF) for integrated civilian navigation system,” in Proceedings of the IEEE/ION Position, Location and Navigation Symposium (PLANS '08), pp. 984–992, Monterey, Calif, USA, May 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Cheng, D. Chen, R. Landry Jr., L. Zhao, and D. Guan, “An adaptive unscented kalman filtering algorithm for MEMS/GPS integrated navigation systems,” Journal of Applied Mathematics, vol. 2014, Article ID 451939, 8 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  15. K.-W. Chiang and Y.-W. Huang, “An intelligent navigator for seamless INS/GPS integrated land vehicle navigation applications,” Applied Soft Computing Journal, vol. 8, no. 1, pp. 722–733, 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. A. Noureldin, A. El-Shafie, and M. R. Taha, “Optimizing neuro-fuzzy modules for data fusion of vehicular navigation systems using temporal cross-validation,” Engineering Applications of Artificial Intelligence, vol. 20, no. 1, pp. 49–61, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. L. Semeniuk and A. Noureldin, “Modeling of INS position and velocity errors using radial basis function neural networks for INS/GPS integration,” in Proceedings of the ION National Technical Meeting, pp. 18–20, Monterey, Calif, USA, January 2006.
  18. A. Noureldin, A. El-Shafie, and M. Bayoumi, “GPS/INS integration utilizing dynamic neural networks for vehicular navigation,” Information Fusion, vol. 12, no. 1, pp. 48–57, 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Škaloud, Optimizing georeferencing of airborne survey systems by INS/DGPS [Ph.D. thesis], Department of Geomatics Engineering, Alberta, Canada, 1999.
  20. Y. Bar-Shalom, X. R. Li, and T. Kirubarajan, Estimation with Applications to Tracking and Navigation: Theory Algorithms and Software, John Wiley & Sons, New York, NY, USA, 2004.
  21. B. Sadeghi and B. Moshiri, “Second-order EKF and unscented Kalman filter fusion for tracking maneuvering targets,” in Proceedings of the IEEE International Conference on Information Reuse and Integration (IEEE IRI '07), pp. 514–519, IEEE, Las Vegas, Nev, USA, August 2007. View at Publisher · View at Google Scholar · View at Scopus
  22. R. Ardito, C. Comi, A. Corigliano, and A. Frangi, “Solid damping in micro electro mechanical systems,” Meccanica, vol. 43, no. 4, pp. 419–428, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  23. A. Kumar and D. Chakraborty, “Effective properties of thermo-electro-mechanically coupled piezoelectric fiber reinforced composites,” Materials & Design, vol. 30, no. 4, pp. 1216–1222, 2009. View at Publisher · View at Google Scholar · View at Scopus
  24. M. Kleiber and T. D. Hien, The Stochastic Finite Element Method: Basic Perturbation Technique and Computer Implementation, Wiley-Interscience, 1992. View at MathSciNet
  25. M. Kamiński and A. Corigliano, “Sensitivity, probabilistic and stochastic analysis of the thermo-piezoelectric phenomena in solids by the stochastic perturbation technique,” Meccanica, vol. 47, no. 4, pp. 877–891, 2012. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  26. M. El-Diasty and S. Pagiatakis, “A rigorous temperature-dependent stochastic modelling and testing for MEMS-based inertial sensor errors,” Sensors, vol. 9, no. 11, pp. 8473–8489, 2009. View at Publisher · View at Google Scholar · View at Scopus
  27. P. Lavoie, Système de Navigation Hybride GPS/INS à Faible Coût pour la Navigation Robuste en Environnement Urbain, M. Ing., Génie Électrique, École de Technologie Supérieure, Montreal, Canada, 2012.
  28. S. Nassar, K.-P. Schwarz, N. El-Sheimy, and A. Noureldin, “Modeling inertial sensor errors using autoregressive (AR) models,” Navigation, vol. 51, no. 4, pp. 259–268, 2004. View at Google Scholar · View at Scopus
  29. S. Nassar, K.-P. Schwarz, N. El-Sheimy, and A. Noureldin, “Modeling inertial sensor errors using autoregressive (AR) models,” Navigation, Journal of the Institute of Navigation, vol. 51, no. 4, pp. 259–268, 2004. View at Google Scholar · View at Scopus
  30. C. H. Kang, S. Y. Kim, and C. G. Park, “Improvement of a low cost MEMS inertial-GPS integrated system using wavelet denoising techniques,” International Journal of Aeronautical and Space Sciences, vol. 12, no. 4, pp. 371–378, 2011. View at Publisher · View at Google Scholar · View at Scopus
  31. N. El-Sheimy, S. Nassar, and A. Noureldin, “Wavelet de-noising for IMU alignment,” IEEE Aerospace and Electronic Systems Magazine, vol. 19, no. 10, pp. 32–39, 2004. View at Publisher · View at Google Scholar · View at Scopus
  32. F. Jiancheng and Y. Sheng, “Study on innovation adaptive EKF for in-flight alignment of airborne POS,” IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 4, pp. 1378–1388, 2011. View at Publisher · View at Google Scholar · View at Scopus
  33. J. Ma, S. Ni, W. Xie, and W. Dong, “An improved strong tracking multiple-model adaptive estimation: a fast diagnosis algorithm for aircraft actuator fault,” Transactions of the Institute of Measurement and Control, 2015. View at Publisher · View at Google Scholar
  34. D. Bhatt, P. Aggarwal, V. Devabhaktuni, and P. Bhattacharya, “A new source difference artificial neural network for enhanced positioning accuracy,” Measurement Science and Technology, vol. 23, no. 10, Article ID 105101, 2012. View at Publisher · View at Google Scholar · View at Scopus
  35. L. M. Bergasa, J. Nuevo, M. A. Sotelo, R. Barea, and M. E. Lopez, “Real-time system for monitoring driver vigilance,” IEEE Transactions on Intelligent Transportation Systems, vol. 7, no. 1, pp. 63–77, 2006. View at Publisher · View at Google Scholar · View at Scopus
  36. R. Vershynin, “How close is the sample covariance matrix to the actual covariance matrix?” Journal of Theoretical Probability, vol. 25, no. 3, pp. 655–686, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus