Transactions of the Korean Society of Automotive Engineers (한국자동차공학회논문집)

The Korean Society of Automotive Engineers (한국자동차공학회)
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Synchronous Interfusion of the Compensatory Filters Based on Multi-rate Sensors for the Control of the Autonomous Vehicle

자율주행 차량 제어를 위한 다중 주기 센서 기반의 상보 필터 동기 융합

  • Received : 2013.10.31
  • Accepted : 2014.02.07
  • Published : 2014.04.01
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Abstract

This paper presents about multi-rate sensors' synchronization and filter fusion via a sigmoid function of the Kalman filter. To synchronize multi-rate sensors, the estimation states of the Kalman filter is modified. A specific matrix that makes the filter choose sensor values only updated is multiplied to measurement matrix. For the filter that has weak points on some criteria, filter fusion is suggested by using sigmoid function. Modified kalman filter is tested with practical case. A sigmoid function was designed for the test and the performance of the modified function is estimated with respect to conventional Kalman filter. Unscented Kalman filter is used to the base filter of the suggested filter because of its stability.

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References

  1. E. Abbot and D. Powell, "Land-vehicle Navigation Using GPS," Proceedings of the IEEE, Vol.87, No.1, pp.145-162, 1999. https://doi.org/10.1109/5.736347
  2. P. Zhang, J. Gu, E. E. Milios and P. Huynh, "Navigation with IMU/GPS/Digital Compass with Unscneted Kalman Filter," International Conference on Mechatronics & Automation, pp.1497-1502, 2005.
  3. C. Hu, W. Chen, Y. Chen and D. Liu, "Adaptive Kalman Filtering for Vehicle Navigation," Journal of Global Positioning Systems, Vol.2, No.1, pp.42-47, 2003. https://doi.org/10.5081/jgps.2.1.42
  4. O. Maklouf, A. Ghila and A. Abdulla, "Cascade Kalman Filter Configuration for Low Cost IMU \/GPS Integration in Car Navigation Like Robot," World Academy of Science Engineering and Technology, Vol.66, No.1, pp.602-609, 2012.
  5. S. Shoval, I. Zeitoun and E, Lenz, "Implementation of a Kalman Filter in Positioning for Autonomous Vehicles," International Journal of Advanced Manufacturing Technology, Vol.13, No.1, pp.738-746, 1997. https://doi.org/10.1007/BF01179074
  6. D. Park, D. Lee, D. Lee, J. Kwon and T. You, "Development and Evaluation of Vehicle Position Estimation using Odometry with Kalman Filter," KSAE Annual Conference Proceedings, pp.1240-1244, 2011.
  7. D. J. Kim, M. K. Kim, K. S. Lee, H. G. Park and M. H. Lee, "Localization System of Autonomous Vehicle via Kalman Filtering," International Conference on Control, Automation and Systems, pp.934-937, 2011.
  8. L. Drolet, F. Michaud and J. Cote, "Adaptable Sensor Fusion Using Multiple Kalman Filters," Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vol.2, pp.1434-1439, 2000.
  9. S. I. Roumeliotis and G. A. Bekey, "An Extended Kalman Filter for Frequent Local and Infrequent Global Sensor Data Fusion," International Symposium on Intelligent Systems and Advanced Manufacturing, 1997.
  10. T. G. Lee, "Centralized Kalman Filter with Adaptive Measurement Fusion," International Journal of Control, Automation and Systems, Vol.1, No.4, pp.444-452, 2003.
  11. A. M. Sabantini, "Quaternion-based Extended Kalman Filter for Determining Orientation by Inertial and Magnetic Sensing," IEEE Transactions on Biomedical Engineering, Vol.53, No.7, pp.1346-1356, 2006. https://doi.org/10.1109/TBME.2006.875664
  12. V. Subramanian, T. F. Burks and W. E. Dixon, "Sensor Fusion Using Fuzzy Logic Enhanced Kalman Filter for Autonomous Vehicle Guidance in Citrus Groves," Transactions of the American Society of Agricultural and Biological Engineers, Vol.52, No.5, pp.1411-1422, 2009.
  13. J. L. Crassidis, "Sigma-point Kalman Filtering for Integrated GPS and Inertial Navigation," IEEE Transactions on Aerospace and Electronics Systems, Vol.42, No.2, pp.750-756, 2006. https://doi.org/10.1109/TAES.2006.1642588
  14. D. M. Mayhew, Multi-rate Sensor Fusion for GPS/Navigation Using Kalman Filtering, M. S. Thesis, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 1999.
  15. A. Smyth and M. Wu, "Multi-rate Kalman Filtering for the Data Fusion of Displacement and Acceleration Response Measurements Dynamic System Monitoring," Mechanical Systems and Signal Processing, Vol.21, No.2, pp.706-723, 2007. https://doi.org/10.1016/j.ymssp.2006.03.005
  16. S. J. Julier, J. K. Uhlmann and H. F. Durrant-Whyte, "A New Approach for Filtering Nonlinear Systems," Proceedings of the American Control Conference, 1995.
  17. Korean Road Traffic Authority, Traffic Accident Factors Analysis 2012 Editions, pp.14-20, 2012.