Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015, Article ID 581909, 12 pages
http://dx.doi.org/10.1155/2015/581909
Research Article

A Fault-Tolerant Filtering Algorithm for SINS/DVL/MCP Integrated Navigation System

1Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science & Engineering, Southeast University, Nanjing 210096, China
2Industrial Center, Nanjing Institute of Technology, Nanjing 211167, China
3Henan University of Technology, Zhengzhou 450007, China

Received 3 July 2014; Revised 13 April 2015; Accepted 15 April 2015

Academic Editor: Filippo Ubertini

Copyright © 2015 Xiaosu Xu 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. R. McEwen, H. Thomas, D. Weber, and F. Psota, “Performance of an AUV navigation system at arctic latitudes,” IEEE Journal of Oceanic Engineering, vol. 30, no. 2, pp. 443–454, 2005. View at Publisher · View at Google Scholar · View at Scopus
  2. P. Ridao, D. Ribas, E. Hernandez, and A. Rusu, “USBL/DVL navigation through delayed position fixes,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '11), pp. 2344–2349, Shanghai, China, May 2011. View at Publisher · View at Google Scholar · View at Scopus
  3. B. Jalving, K. Gade, K. Svartveit, A. Willumsen, and R. Sørhagen, “DVL velocity aiding in the HUGIN 1000 integrated inertial navigation system,” Modeling, Identification and Control, vol. 25, no. 4, pp. 223–235, 2004. View at Publisher · View at Google Scholar · View at Scopus
  4. T. Zhang and X. Xu, “A new method of seamless land navigation for GPS/INS integrated system,” Measurement, vol. 45, no. 4, pp. 691–701, 2012. View at Publisher · View at Google Scholar · View at Scopus
  5. L. Paull, S. Saeedi, M. Seto, and H. Li, “AUV navigation and localization: a review,” IEEE Journal of Oceanic Engineering, vol. 39, no. 1, pp. 131–149, 2014. View at Publisher · View at Google Scholar · View at Scopus
  6. M. J. Dove, “Kalman filter techniques in marine integrated navigation systems,” Journal of Navigation, vol. 30, no. 1, pp. 135–145, 1977. View at Publisher · View at Google Scholar
  7. S. A. Broatch and A. J. Henley, “An integrated navigation system manager using federated Kalman filtering,” in Proceedings of the IEEE National Aerospace and Electronics Conference (NAECON '91), pp. 422–426, Dayton, Ohio, USA, May 1991. View at Scopus
  8. X.-Y. Chen, J. Yu, and X.-F. Zhu, “Theoretical analysis and application of Kalman filters for ultra-tight global position system/inertial navigation system integration,” Transactions of the Institute of Measurement and Control, vol. 34, no. 5, pp. 648–662, 2012. View at Publisher · View at Google Scholar · View at Scopus
  9. T. Xu, “Adaptive Kalman filter for INS/GPS integrated navigation system,” in Proceedings of the 2nd International Conference on Measurement, Instrumentation and Automation, vol. 336–338, pp. 332–335, Guilin, China, April 2013.
  10. T. Abdelazim, W. Abdel-Hamid, N. El-Sheimy, and E. H. Shin, “Experimental results of an adaptive fuzzy network Kalman filtering integration for low cost navigation applications,” in Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies (NAFIPS '04), pp. 844–849, Banff, Canada, June 2004. View at Scopus
  11. H. Yanling, Z. Yi, and S. Feng, “An anomaly recognition algorithm for DVL,” in Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA '11), pp. 2423–2427, IEEE, Beijing, China, August 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. Y. Zhang, Y. Ding, and N. Li, “A tightly integrated SINS/DVL navigation method for autonomous underwater vehicle,” in Proceedings of the 5th International Conference on Computational and Information Sciences (ICCIS '13), pp. 1107–1110, Shiyan, China, June 2013. View at Publisher · View at Google Scholar · View at Scopus
  13. K.-H. Tang, M.-M. Jiang, and J. Weng, “Design of SINS/Phased Array DVL integrated navigation system for underwater vehicle based on adaptive filtering,” Journal of Chinese Inertial Technology, vol. 21, no. 1, pp. 65–70, 2013 (Chinese). View at Google Scholar · View at Scopus
  14. Ø. Hegrenaes and O. Hallingstad, “Model-aided INS with sea current estimation for robust underwater navigation,” IEEE Journal of Oceanic Engineering, vol. 36, no. 2, pp. 316–337, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. H. Miller and D. A. Hilts, “Fault tolerant integrated inertial navigation/global positioning systems for next generation spacecraft,” in Proceedings of the IEEE/AIAA 10th Digital Avionics Systems Conference, pp. 207–212, Los Angeles, Calif, USA, October 1991. View at Scopus
  16. T. Zhang, X.-S. Xu, Y. Li, and S.-P. Gong, “AUV Fault-tolerant technology based on inertial navigation and underwater acoustics assisted navigation system,” Journal of Chinese Inertial Technology, vol. 21, no. 4, pp. 512–516, 2013 (Chinese). View at Google Scholar · View at Scopus
  17. M. Ushaq and F. J. Cheng, “A fault tolerant integrated navigation scheme realized through online tuning of weighting factors for Federated Kalman Filter,” Applied Mechanics and Materials, vol. 446-447, pp. 1078–1085, 2014. View at Publisher · View at Google Scholar · View at Scopus
  18. D. B. Fogel, “Introduction to simulated evolutionary optimization,” IEEE Transactions on Neural Networks, vol. 5, no. 1, pp. 3–14, 1994. View at Publisher · View at Google Scholar · View at Scopus
  19. A. F. Tappenden and J. Miller, “A novel evolutionary approach for adaptive random testing,” IEEE Transactions on Reliability, vol. 58, no. 4, pp. 619–633, 2009. View at Publisher · View at Google Scholar · View at Scopus
  20. M. L. M. Víctor, C. Vicent, L. Luis, and F. Anta Antonio, “A model of self-avoiding random walks for searching complex networks,” Networks, vol. 60, no. 2, pp. 71–85, 2012. View at Google Scholar · View at MathSciNet
  21. J. Du and R. Rada, “Dilemmas in knowledge-based evolutionary computation for financial investing,” Intelligent Decision Technologies, vol. 7, no. 2, pp. 123–136, 2013. View at Publisher · View at Google Scholar · View at Scopus
  22. M. Mahsal Khan, A. Masood Ahmad, G. Muhammad Khan, and J. F. Miller, “Fast learning neural networks using Cartesian genetic programming,” Neurocomputing, vol. 121, pp. 274–289, 2013. View at Publisher · View at Google Scholar · View at Scopus
  23. C. Xilin, “Neural network combined with evolutionary algorithm for Knowledge management in Electricity Supply Industry,” in Proceedings of the IEEE International Symposium on Test and Measurement (ICTM '09), vol. 2, pp. 355–358, Hong Kong, 2009.
  24. N. Mehdiyev and D. Enke, “Interest rate prediction: a neuro-hybrid approach with data preprocessing,” International Journal of General Systems, vol. 43, no. 5, pp. 535–550, 2014. View at Publisher · View at Google Scholar
  25. F. Zha, B.-Q. Hu, and J. Liu, “Prediction of gyro motor's state based on grey theory and BP neural network,” Journal of Chinese Inertial Technology, vol. 18, no. 1, pp. 120–123, 2010 (Chinese). View at Google Scholar · View at Scopus
  26. G. Jing, W. Du, and Y. Guo, “Studies on prediction of separation percent in electrodialysis process via BP neural networks and improved BP algorithms,” Desalination, vol. 291, pp. 78–93, 2012. View at Publisher · View at Google Scholar · View at Scopus
  27. Z. Haodong and L. Hongchan, “Optimized BP neural network model based on niche genetic algorithm,” in Proceedings of the 2nd International Conference on Green Communications and Networks, vol. 223 of Lecture Notes in Electrical Engineering, pp. 219–226, Springer, 2013. View at Google Scholar
  28. L. Tian, Y. Luo, and Y. Wang, “Prediction model of TIG welding seam size based on BP neural network optimized by genetic algorithm,” Journal of Shanghai Jiaotong University, vol. 47, no. 11, pp. 1690–1696, 1701, 2013 (Chinese). View at Google Scholar · View at Scopus
  29. H. Yang, R. S. Fan, and D. H. Xu, “Power information system risk assessment method based on genetic algorithms and neural network,” Applied Mechanics and Materials, vol. 530-531, pp. 429–433, 2014. View at Publisher · View at Google Scholar · View at Scopus
  30. H. Wei, Theory and Method of the Neural Network Structure Design, National Defence of Industry Press, Beijing, China, 2005.
  31. P.-J. Li, X.-S. Xu, L.-H. Wang, and Y. Li, “Design of intelligent fault-tolerant to passive underwater integrated navigation system,” Journal of Chinese Inertial Technology, vol. 21, no. 2, pp. 221–225, 2013 (Chinese). View at Google Scholar · View at Scopus