Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Smoothing and Prediction of Measurement in INS/GPS Integrated Kalman Filter

INS/GPS 결합 칼만필터의 측정치 스무딩 및 예측

  • Published : 2001.11.01
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Abstract

Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.

Keywords

References

  1. M. M. Kuritsky and M. S. Goldstein, 'Inertial navigation,' Pro. of IEEE, vol. 71, no. 10, pp. 1156-1176, Oct., 1983
  2. G. M. Siouris, Aerospace Avionics Systems, Academic Press, 1993
  3. O. Salychev, Inertial System in Navigation and Geophysics, Bauman MSTU Press Moscow, 1998
  4. S. H. Stovall, Basic inertial navigation, Naval air warfare weapons division, 1997
  5. R. L. Greenspan, 'Inertial navigation technology from 1970-1995,' Navigation: journal of the Institute of navigation vol. 42, no. 1, pp. 165-185, 1995
  6. D. H. Titerton and J. L. Weston, Strapdown inertial navigation technology, Peper Peregrinus Ltd, 1997
  7. P. H. Dana, Global positioning system overview, University of Texas, 1994
  8. C. D. Evans, Design and Analysis of integrated navigation systems using real INS and GPS data, AFIT/GE/ENG, 1994
  9. R. M. Rogers, 'Kalman Filter inertial navigation system error model based on filter consideration,' AIAA-94-3547, cp, pp. 65-70, 1994
  10. P. S. Maybeck, Stochastic, models, estimation and Control volume 1, Academic Press, 1979