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Volume 2018, Article ID 3039061, 7 pages
https://doi.org/10.1155/2018/3039061
Research Article

Application of Federal Kalman Filter with Neural Networks in the Velocity and Attitude Matching of Transfer Alignment

Electronic Information and Control Engineering College, Xi’an University of Architecture and Technology, Xi’an 710055, China

Correspondence should be addressed to Zhongxing Duan; moc.361@naud_xhz

Received 8 July 2017; Accepted 8 October 2017; Published 21 January 2018

Academic Editor: Junpei Zhong

Copyright © 2018 Lijun Song 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. X.-J. Guan and X.-L. Wang, “Transfer alignment match methods for strapdown inertial navigation system on moving bases,” Aero Weapons, vol. 4, no. 2, pp. 3–8, 2014. View at Google Scholar
  2. G.-l. Yang, L.-f. Wang, E.-k. Yuan, L. Cai, and L.-w. Qiao, “Rapid transfer alignment for carrier - based aircrafts in catapult,” in Ship Science and Technolog, vol. 36, pp. 50–54, 3 edition, 2014. View at Google Scholar
  3. L. Zhang, S. Qian, S. Zhang, and H. Cai, “Federated nonlinear predictive filtering for the gyroless attitude determination system,” Advances in Space Research, vol. 58, no. 9, pp. 1671–1681, 2016. View at Publisher · View at Google Scholar · View at Scopus
  4. Q. Y. yuan and N. I. Huifang, “Application of federated filtering theory to designing integrated navigation system,” Journal of Chinese Inertial Technology, vol. 5, no. 3, pp. 1–5, 1997. View at Google Scholar
  5. C. Yang, Y. Jiang, Z. Li, W. He, and C.-Y. Su, “Neural control of bimanual robots with guaranteed global stability and motion precision,” IEEE Transactions on Industrial Informatics, 2017. View at Publisher · View at Google Scholar
  6. L. Dan, “Improved BP neural network WSN data fusion scheme,” Information Technology, vol. 37, no. 2, pp. 155–160, 2017. View at Google Scholar
  7. C. Yang, J. Luo, Y. Pan, Z. Liu, and C. Y. Su, “Personalized variable gain control with tremor attenuation for robot teleoperation,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1–12, 2017. View at Publisher · View at Google Scholar
  8. M. Yongjun, X. Yonghao, L. Yang, and L. Yajun, “Data aggregation algorithm based on the model of deep learning,” Journal of Tianjin University of Science Technology, vol. 32, no. 4, pp. 1–5, 2017. View at Google Scholar
  9. C. Yang, K. Huang, H. Cheng, Y. Li, and C.-Y. Su, “Haptic identification by ELM-controlled uncertain manipulator,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 8, pp. 2398–2409, 2017. View at Publisher · View at Google Scholar
  10. T. Zengshan and C. Yongquan, “Attitude measurement fusion algorithm in GPS/SINS based on BP neural-network,” Journal of Chongqing University of Posts and Telecommunications, vol. 26, no. 4, pp. 478–482, 2014. View at Google Scholar
  11. X. Tianlai and M. Xu, “INS/GPS integrated navigation method based on elman neural network,” in Proceedings of the International Conference on Fuzzy Systems and Neural Computing, pp. 310–313, 2011.
  12. B. Feng, H. Ma, M. Fu, and C. Yang, “Real-time state estimator without noise covariance matrices knowledge-fast minimum norm filtering algorithm,” IET Control Theory & Applications, vol. 9, no. 9, pp. 1422–1432, 2015. View at Publisher · View at Google Scholar · View at Scopus
  13. G.-M. Yan, J. Weng, P.-X. Yang, and Y.-y. Qin, “Study on SINS rapid gyrocompass initial alignment,” International Symposium on Inertial Technology and Navigation, pp. 323–330, 2010. View at Google Scholar
  14. K. Kim, S. Seol, and S.-H. Kong, “High-speed train navigation system based on multi-sensor data fusion and map matching algorithm,” International Journal of Control, Automation, and Systems, vol. 13, no. 3, pp. 503–512, 2015. View at Publisher · View at Google Scholar · View at Scopus
  15. C. Yang, X. Wang, Z. Li, Y. Li, and C. Su, “Teleoperation control based on combination of wave variable and neural networks,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 8, pp. 2125–2136, 2017. View at Publisher · View at Google Scholar
  16. L. Bin, The research and design of transfer alignment simulation and verification system on ship carried weapon inertial navigation system, Harbin Engineering University, Harbin, China, 2012.