대한조선학회논문집 (Journal of the Society of Naval Architects of Korea)

  • 제45권3호
  • /
  • Pages.269-279
  • /
  • 2008
  • /
  • 1225-1143(pISSN)
  • /
  • 2287-7355(eISSN)
대한조선학회 (The Society of Naval Architects of Korea)
권호 표지
DOI QR코드

DOI QR Code

적응 이동 구간 칼만 필터를 이용한 무인 잠수정의 항법 시스템에 관한 연구

A Study on the Underwater Navigation System with Adaptive Receding Horizon Kalman Filter

  • 조경남 (서울대학교 해양기술인력양성사업단) ;
  • 서동철 (서울대학교 조선해양공학과) ;
  • 최항순 (서울대학교 해양시스템 공학연구소)
  • Jo, Gyung-Nam (Marine Technology Education and Research Center, Seoul National University) ;
  • Seo, Dong-C. (Department of Naval Architecture and Ocean Engineering, Seoul National University) ;
  • Choi, Hang-S. (Research Institute of Marine Systems Engineering, Seoul National University)
  • 발행 : 2008.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper, an underwater navigation system with adaptive receding horizon Kalman filter (ARHKF) is studied. It is well known that incorrect statistical information and temporal disturbance invoke errors of any navigation systems with Kalman filter, which makes the autonomous navigation difficult in real underwater environment. In this context, two kinds of problems are herein considered. The first one is the development of an algorithm, which estimates the noise covariance of a linear discrete time-varying stochastic system. The second one is the implementation of ARHKF to underwater navigation systems. The performance of the derived estimation algorithm of noise covariance and the ARHKF are verified by simulation and experiment in the towing tank of Seoul National University.

키워드

참고문헌

  1. Choi, B.Y. and Bien, Z., 1989, “Sliding-Windowed Weighted Recursive Least-Squares Method for Parameter Estimation,” IEEE Electronics Letters, Vol. 25, No. 20, pp. 1381-1382 https://doi.org/10.1049/el:19890924
  2. Chung, D.H., Lee, J.G., Park, C.G. and Park, H.W. 1996, “Strapdown INS Error Model for Multiposition Alignment,” IEEE Trans. on Aerospace and Electronic Systems, Vol. 32, No. 4, pp. 1362-1366 https://doi.org/10.1109/7.543857
  3. Jo, G. and Choi, H.S. 2004, “ Underwater Navigation System with Velocity Measurement by a Receding Horizon Kalman Filter,” IEEE/MTS proc. of Underwater Technology 04, pp. 1612-1619
  4. Jo, G.N., Seo, D.C. and Choi, H.S., 2006a, “Underwater Navigation System with Velocity Reference Using a Receding Horizon Kalman Filter,” Proc. of the Annual Spring Meeting the SNACK, 2006, pp. 727-732
  5. Jo, G. and Choi, H.S., 2006b, “Velocity-Aided Underwater Navigation System Using Receding Horizon Kalman Filter,” Journal of Oceanic Engineering. Vol. 31, No. 3, pp. 565-573 https://doi.org/10.1109/JOE.2006.875100
  6. Jo, G., 2007a, A Study of Adaptive Receding Horizon Kalman Filter for Underwater Navigation Systems, Ph. D. Dissertation, Seoul National University
  7. Jo, G., Seo, D.C. and Choi, H.S., 2007b, “A Study of the Estimation of Noise Covariance for Unmanned Underwater Vehicles with Adaptive Receding Horizon Kalman Filter,” Proc. of the Annual Spring Meeting the SNACK 2007, pp. 1040-1047
  8. Lee, D.Y. and Ha M.K., 2003, “A Study on the Design Parameters of Controller for Dynamic Positioning System,” Journal of Society of Naval Architects of Korea, Vol. 40, No. 1, pp. 8-19
  9. Lee, J.M., Lee P.M. and Seoung, W.J. 2003, “Underwater Hybrid Navigation Algorithm Based on an Ineritial Sensor and a Doppler velocity Log Using an Indirect Feedback Kalman Filter,” Journal of Korean Society of Ocean Engineering, Vol. 17, No. 6, pp. 83-90
  10. Lee P.M., Jeon, B.W., Kim, S.M., Lee, J.M., Rheem Y.G. and Yang, S.I., 2004, “A Hybrid Navigation System for Underwater Unmanned Vehicles using a Range Sonar” , Journal of Korean Society of Ocean Engineering, Vol. 18, No. 4, pp. 33-39
  11. Lee, P.M., Jeon, B.W., Kim, S.M., Choi, H.T., Lee J.M. and Kim K.H., 2005, “Convergence of Initial Estimation Error in a Hybrid Underwater Navigation System with a Range Sonar,” Journal of Korean Society of Ocean Engineering, Vol. 19, No. 6, pp. 78-85
  12. Manolakis, D.G., Ling, F. and Proakis, J.G. , 1987, “Efficient Time-Recursive Least-Square Algorithms for Finite Memory Adaptive Filtering,” IEEE Trans. on Circuits system, Vol. 34, No. 4, pp. 400-108 https://doi.org/10.1109/TCS.1987.1086148
  13. Park, J.G., Lee , J.G., Kim, J.W. and Park, C. G., 2000, “Observability Analysis of SDINS In- Flight Alignment,” Proc. of ION GPS 2000, Salt Lake City, Utah, pp. 19-22
  14. Sayed, A.H., 2003, Fundamentals of Adaptive Filtering. Wiley-Interscience, USA
  15. Yoon, H.K. and Rhee, K.P. 2001, “Estimation of External Forces and Current Variables in Sea Trial by Using the Estimation-Before- Modeling Method,” Journal of Society of Naval Architects of Korea, Vol. 38, No. 4, pp. 30-38
  16. Yoon, H.K. and Rhee, K.P., 2003, “Comparison of the Estimation-Before- Modeling Technique with the Parameter Estimation Method Using the Extended Kalman Filter in the Estimation of Manoeuvring Derivatives of a Ship,” Journal of the Society of Naval Architects of Korea, Vol. 40, No. 5, pp. 43-52 https://doi.org/10.3744/SNAK.2003.40.5.043
  17. Zhang, Y. and Jiang, J., 2004, “A Novel Variable-length Sliding Window Blockwise Least-squares Algorithm for On-line Estimation of Time-varying Parameters,” International Journal of Adaptive Control and Signal Processing, Vol. 18, No. 6, pp. 505-521 https://doi.org/10.1002/acs.811