The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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EKF Based Outdoor Positioning System using Multiple GPS Receivers

다중 GPS를 이용한 EKF 기반의 실외 위치 추정 시스템

  • Received : 2013.01.08
  • Accepted : 2013.03.26
  • Published : 2013.05.31
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Abstract

In this paper, a high precision outdoor positioning system is newly proposed using multiple GPS receivers based on the Extended Kalman Filter (EKF). Typically, the GPS signal has the instantaneous errors that degrade the positioning seriously. Using the multiple GPS receivers instead of an expensive DGPS receiver, the positioning reliability and accuracy are improved in this research as a low cost solution. To incorporate the small displacement, an INS data have been tightly coupled to the GPS data, which has the inherit disadvantage of the cumulative error occurring over time. To achieve a stabilized and accurate positioning system, the multiple GPS receiver data are fused with the INS data through the EKF process. Through real navigation experiments of an outdoor mobile robot, the performance of the proposed system has been verified to be accurate comparable to DGPS system with a lower cost.

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References

  1. J. H. Lee and H. S. Kim, "A Study of High Precision Position Estimator Using GPS/INS Sensor Fusion", Journal of The Institute of Electronics Engineers of Korea, vol. 49, no. 11, November 2012. https://doi.org/10.5573/ieek.2012.49.11.159
  2. S. H. Oh, D. H. Hwang, C. S. Park and S. J. Lee, "Attitude Determination GPS/INS Integration System Design Using Triple Difference Technique", Journal of Electrical Engineering & Technology, vol. 7, no. 4, pp. 615-625, July 2012. https://doi.org/10.5370/JEET.2012.7.4.615
  3. Kai-Wei Chiang and Yun-Wen Huang, "An intelligent navigator for seamless INS/GPS integrated land vehicle navigation applications," Applied Soft Computing, pp. 722-733, May 2007.
  4. Kazunori Ohno , Takashi Tsubouchi, Bunji Shigematsu, Shoichi Maeyama and Shin'ichi Yuta, "Outdoor Navigation of a Mobile Robot between Buildings based on DGPS and Odometry Data Fusion," IEEE International Conference on Robotics & Automation, vol. 2, pp. 1978-1984, September 2003.
  5. H. C. Moon, Y. J. Son and J. H. Kim, "The Development of Driving Algorithm for an Unmanned Vehicle with Multiple-GPS's," Robotics and Systems, vol. 14, no. 1, January 2008.
  6. Roozbeh Mottaghi, Michael Kaess, Ananth Ranganathan, Richard Roberts and Frank Dellaert, "Place Recognitionbased Fixed-Lag Smoothing for Environments with Unreliable GPS," IEEE International Conference on Robotics and Automation, pp. 1862-1867, May 2008.
  7. J. M. Kim, Y. T. Kim and S. S. Kim, "An accurate localization for mobile robot using extended Kalman filter and sensor fusion," IEEE International Joint Conference on Neural Networks, pp. 2928-2933, June 2008.
  8. Jun Zhou and Hamidreza Bolandhemmat, "Integrated INS/GPS System for an Autonomous Mobile Vehicle," IEEE International Conference on Mechatronics and Automation, pp. 694-699, August 2007.
  9. Dongliang Huang, "Expectation Maximization Based GPS/INS Integration for Land-Vehicle Navigation," IEEE Transaction on Aerospace and Electornic Systems, vol. 43, no. 3 July 2007.
  10. K. G. Kim, C. H. Park, M. J. Yu and Y. B. Park, "A Performance Comparison of Extended and Unscented Kalman Filter for INS/GPS Tightly Coupled Approach", Journal of Control, Automation, and Systems Engineering, vol. 12, no. 8, August 2006.
  11. Yunchun Yang and Jay A. Farrell, "Magnetometer and Differential Carrier Phase GPS-Aided INS for Advanced Vehicle Control," IEEE Trans. On Robotics and Automation, vol. 19, no. 2, April 2003.

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