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Study for Real-Time Ability of INS/CNS/GNSS Integrated Navigation Method

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INS/CNS/GNSS Integrated Navigation Technology

Abstract

Real-time performance is also one of the important indexes to measure its performance besides requirements for navigation precision during the engineering application of the integrated navigation method of ship inertial navigation system (SINS), celestial navigation system (CNS), and global navigation satellite system (GNSS). During the improvement of the SINS/CNS/GNSS integrated navigation system performance, on one hand, navigation precision may be improved greatly by making the best of all and through collaborative transcendence due to the diversity of observation means, but system dimension and measurement dimension of the system will be increased simultaneously, which will then increase the amount of filtering computation. On the other hand, it is sometimes required to design several filters since observation information of a navigation subsystem is nonsynchronous, and the output frequency is inconsistent, which further increases the difficulty of navigation computer data processing[1–2].

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References

  1. Yuan X, Yu J, Chen Z (1993) Navigation System. Aviation Industry Press, Beijing

    Google Scholar 

  2. Zhang G, Zeng J (2008) The principle and technology integrated navigation. Xi’an Jiaotong University Press, Xi’an

    Google Scholar 

  3. Wan D, Fang J (1998) Inertial navigation initial alignment. Southeast University Press, Nanjing

    Google Scholar 

  4. Wu H, Yu W, Fang J (2005) Research on reduced dimension model of SINS/CNS integrated navigation system[J]. Aerosp Control 23(6):12–16

    Google Scholar 

  5. Walton RW (2000) Real time, high accuracy, relative state estimation for multiple vehicle systems. Department of Mechanical Engineering, University of California, Los Angeles

    Google Scholar 

  6. Goshen-Meskin D, Bar-Itzhack IY (1992) Observability analysis of piece-wise constant system-part I: theroy. IEEE Trans Aerosp Electron Syst 28(4):1056–1067

    Article  MathSciNet  Google Scholar 

  7. Goshen-Meskin D, Bar-Itzhack IY (1992) Observability analysis of piece-wise constant system-Part II: application to inertial navigation in-flight alignment. IEEE Trans Aerosp Electron Syst 28(4):1068–1075

    Article  MathSciNet  Google Scholar 

  8. Cheng X, Wan D, Zhong X. (1997) Study on observability and its degree of strapdown inertial navigation system[J]. J Southeast Univ 27(6):6–11

    Google Scholar 

  9. WU H, YU W, Fang J (2006) Simulation of SINS/CNS integrated navigation system used on high altitude and long-flight-time unpiloted aircraft[J]. Acta Aeronautica et Astronautica Sinica 27(2):299–304

    Google Scholar 

  10. Shuai P, Chen D, Jiang Y (2004) Observable degree analysis method of integrated GPS/INS navigation system[J]. J Astronaut (4):219–224

    Google Scholar 

  11. He X, Liu J, Yuan X (1997) Design of the reduced order filter for the integrated GPS/INS[J]. J Astronaut 5(2):1–3

    Google Scholar 

  12. Dong X, Zhang S, Hua Z (1998) Integrated GPS/INS navigation and its applications. National University of Defense Technology Press, Changsha

    Google Scholar 

  13. Huang L, Zhou B, Shan M (2003) MIMU/GPS integrated navigation system based on DSP[J]. J Chin Inert Technol 11(3):12–15

    Google Scholar 

  14. He X, Chen Y, Iz HB (1998) A reduced-order model for integrated GPS/INS. IEEE AES Syst Mag (3):40–45

    Google Scholar 

  15. Fu M, Deng Z, Zhang J (2003) Kalman filtering theory and its application in navigation system

    Google Scholar 

  16. Yi X, He Y, Guan X (2002) Federated filtering algorithm based on different local model[J]. J Chin Inert Technol 10(5):16–19

    Google Scholar 

  17. Carlson NA (1994) Federated Kalman filter simulation results. Navig J ION 41(3):297–321

    Article  Google Scholar 

  18. Julier SJ, Uhlmann JK (1997) A new extension of the Kalman filter to nonlinear systems. The 11th international symposium on aerospace/defense sensing, simulation and controls. Orlando FL, USA

    Google Scholar 

  19. Sheng W, Tan L (2009) Fast data fusion method for MGNC integrated navigation system[J]. J Beijing Univ Aeronaut Astronaut 35(6):657–660

    Google Scholar 

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Correspondence to Wei Quan .

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© 2015 National Defense Industry Press, Beijing and Springer-Verlag Berlin Heidelberg

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Quan, W., Gong, X., Fang, J., Li, J. (2015). Study for Real-Time Ability of INS/CNS/GNSS Integrated Navigation Method. In: INS/CNS/GNSS Integrated Navigation Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45159-5_9

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  • DOI: https://doi.org/10.1007/978-3-662-45159-5_9

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