Skip to main content
SpringerLink
Log in
Book cover

INS/CNS/GNSS Integrated Navigation Technology pp 185–235Cite as

INS/GNSS Integrated Navigation Method

  • Chapter
  • First Online:

  • 2791 Accesses

Abstract

Ship inertial navigation system (SINS) and global navigation satellite system (GNSS) are two kinds of common navigation equipments with respect to the advantages and disadvantages during application. The former has strong autonomy, high short-term precision, and continuous output, but errors accumulates with time; the latter has high positioning and velocity measurement precision and errors do not accumulate with time, but has incontinuous output information and susceptibility to interference. Integration of the two to realize complementary advantages will significantly improve overall performance of the navigation system. At present, the SINS/GNSS integrated navigation system has been widely used in fields such as aviation, aerospace, and sailing, and it is a relatively ideal integrated navigation system.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Baziw J, Leondes CT (1972) In-flight alignment and calibration of inertial measurement units, Part I: General formulation. IEEE Trans Aerosp Electron Syst 8(4):439–449

    Article  Google Scholar 

  2. Baziw J, Leondes CT (1972) In-flight alignment and calibration of inertial measurement units, Part II: Experimental results. IEEE Trans Aerosp Electron Syst 8(4):450–465

    Article  Google Scholar 

  3. Liu B, Fang Ji (2008) A new adaptive feedback Kalman filter based on observability analysis for SINS/GPS. AcAAS 29(2):430–436

    MathSciNet  Google Scholar 

  4. Qin Y, Zhang H, Wang S (1998) Theory of Kalman filter and integrated navigation. Northwest industrial university press, Xi’an

    Google Scholar 

  5. Geng Y, Cui Z, Zhang H, Fang J (2004) Adaptive fading Kaman filter with applications in integrated navigation system. BUAAJ 30(5):434–437

    Google Scholar 

  6. Chen B, Zhang Y (2001) Error models of inertial navigation system in initial alignment and calibration. Aerosp Shanghai (6):4–8

    Google Scholar 

  7. Dmitriyev SP (1997) Nonlinear filtering methods application in INS alignment. IEEE Trans Aerosp Electron Syst 33(1):260–271

    Article  Google Scholar 

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

    Google Scholar 

  9. Yi G et al (1987) Theory of inertial navigation. Aviation Industry Press, Beijing

    Google Scholar 

  10. Shen Z, Yu W, Fang J (2007) Nonlinear algorithm based on UKF for low-cost SINS/GPS integrated navigation system. Syst Eng Electron 29(3):408–411

    MATH  Google Scholar 

  11. Yu MJ, Lee JG, Park HW (2004) Nonlinear robust observer design for strapdown INS in-flight alignment. IEEE Trans Aerosp Electron Syst 40(3):797–807

    Article  Google Scholar 

  12. Yu MJ, Lee JG, Park HW(1999) Comparison of SDINS in-flight alignment using equivalent error models. IEEE Trans Aerosp Electron Syst 35(3):1046–1053

    Article  Google Scholar 

  13. Geng Y, Guo W, Cui Z, Fang J (2004) Observability on attitude errors in GPS/SINS in-flight alignment. J Chin Inert Technol 12(1):37–42

    Google Scholar 

  14. Lee JG, Yoon YJ, Mark JG (1994) Extension of strapdown attitude algorithm for high-frequency base motion. IEEE Trans Aerosp Electron Syst 30(4):306–310

    Google Scholar 

  15. Wan D, Fang J (1998) Initial alignment of inertial navigation. Southeast university press, Nanjing

    Google Scholar 

  16. Dong X, Zhang S, Hua Z (1998) GPS/INS integrated navigation and its application. National University of Defence Technology Press, Changsha

    Google Scholar 

  17. Lin M, Fang J, Gao G (2003) A new composed kalman filtering method for GPS/SINS integrated navigation system. J Chin Inert Technol 11(3):29–33

    Google Scholar 

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

    Google Scholar 

  19. Shuai P, Cheng D, Jiang Y (2004) Observable degree analysis method of integrated GPS/SINS navigation system. J Astronaut 25(2):219–225

    Google Scholar 

  20. Meskin G, Itzhack B (1992) Observability analysis of piece-wise constant systems, Part I: theory. IEEE Trans Aerosp Electron Syst 28(4):1056–1067

    Article  Google Scholar 

  21. Zhang J, Tan M, Ren S (2003) A cascade SINS/GNSS integrated navigation system with closed loop feedback. J Chin Inert Technol 11(5):12–15

    Google Scholar 

  22. Simon J, Julier JK, Uhlmann H et al (1995) A new approach for filtering nonlinear systems. In: Proceedings of the American Control Conference. American Control Conference, vol 1., IEEE Service Center, Virginia, pp 1628–1632, Seattle, June 1995

    Google Scholar 

  23. Rui Z, Qitai G (2000) Nonlinear filtering algorithm with its application in INS alignment. Proceedings of the tenth IEEE workshop on statistical signal and array processing, 2000, pp 510–513

    Google Scholar 

  24. Liu X, Fang J (2003) An abnormal data eliminating method used in low-dynamic carrier phase DGPS position system. J Chin Inert Technol 11(6):64–68

    MathSciNet  Google Scholar 

  25. Mohamed AH, Schwarz KP (1999) Adaptive Kalman filtering for INS/GPS. J Geod 73(4): 193–203

    Article  MATH  Google Scholar 

  26. Gul F, Fang J, Gaho AA (2006) GPS/SINS navigation data fusion using quaternion model and unscented Kalman filter. 2006 IEEE international conference on mechatronics and automation, 2006, pp 1854–1859

    Google Scholar 

  27. Gaho AA, Fang J, Gul F (2006) GPS/GLONASS/SINS synergistic integration into flight vehicle for optimal navigation solution. 2006 IEEE international conference on mechatronics and automation, 2006, pp 1848–1853

    Google Scholar 

  28. Farrell J, Barth M (1998) The global positioning system and inertial navigation. McGraw-Hill, NewYork

    Google Scholar 

  29. Gong X, Fang J (2009) Application of modified Kalman Filtering restraining outliers based on orthogonality of innovation to POS. AcAAS 30(12):2349–2354

    Google Scholar 

  30. Kalman RE (1960) A new approach to linear filtering and prediction problems. Trans ASME J Basic Eng (82):35–45

    Google Scholar 

  31. Liu H, Yao Y, Lu D et al (2003) Study for outliers based on Kalman filtering. Study Electr Mach Control 7(1):40–42

    Google Scholar 

  32. Haykin S, Liang L (1994) Modified Kalman filtering. IEEE Trans Signal Process 27(1):1239–1242

    Article  Google Scholar 

  33. Liu B, Gong X, Fang J (2007) In-flight self-alignment for airborne SINS/GPS based on GPS observation and model predict filter. J Chin Inert Technol 15(5):568–572

    Google Scholar 

  34. Sheng J, Fu M, Liu Y (2003) Rapid initial alignment of SINS for stationary base with wavelet network. Acta Sci Nat Univ NeiMongol 34(4):468–471

    Google Scholar 

  35. Bevly DM, Parkinson B (2007) Cascaded Kalman filters for accurate estimation of multiple biases, dead-reckoning navigation, and full state feedback control of ground vehicles. IEEE Trans Control Syst Technol 15(2):199–208

    Article  Google Scholar 

  36. Liu Z, Chen Z (2004) Application of condition number in analysis observability of system. J Syst Simul 16(7):1552–1555

    Google Scholar 

  37. Sohne W, Heinze O et al (1994) Integrated INS/GPS system for high precision navigation applications. IEEE Position Location Navigation, 310–313

    Google Scholar 

  38. Meditch J (1973) A survey of data smoothing for linear and nonlinear dynamic systems. Automatica 9:151–162

    Google Scholar 

  39. Simon D (2006) Optimal state estimation: Kalman, H1 and nonlinear approaches. Wiley, NewJersey

    Google Scholar 

  40. Rauch H, Tung F, Striebel C (1965) Maximum likelihood estimates of linear dynamic systems. AIAA Journal 3(8):1445–1450

    Article  MathSciNet  Google Scholar 

  41. Post-processing, software version 8.30 manual. http://www.novatel.com

  42. Gelb A (1974) Applied optimal estimation. MIT Press, Cambridge

    Google Scholar 

  43. Särkkä S, Viikari V et al (2011) Phase-based UHF RFID tracking with nonlinear Kalman filtering and smoothing. Sensors J IEEE 12(5): 904–910

    Article  Google Scholar 

  44. Wan EA, Merwe R Van Der (2000) The unscented Kalman filter for nonlinear estimation. In: Proceedings of the IEEEAS-SPCC, Alta, Oct 2000, pp 153–158

    Google Scholar 

  45. Julier S, Uhlmann J et al (2000) A new method for nonlinear transformation of means and covariances in filters and estimators. IEEE Trans Automat Control 45:477–482

    Article  MATH  MathSciNet  Google Scholar 

  46. Särkkä S (2008) Unscented Rauch-Tung-Striebel smoother. IEEE Trans Automat Control 53(3):845–849

    Article  MathSciNet  Google Scholar 

  47. Goshen-Meskin D, Bar-itzhack IY (1992) Unified approach to inertial navigation system error deling. J GCD 15(3):648–653

    MATH  Google Scholar 

  48. Fang J-c, Gong X-l (2010) Predictive iterated Kalman filter for INS/GPS integration and its application to SAR motion compensation. IEEE Trans Instrum Meas 59(4):909–915

    Google Scholar 

  49. David T, John W (2004) Strapdown inertial navigation technology. The institution of electrical engineers, pp 344–345

    Google Scholar 

  50. Wang Y-f, Sun F-C et al (2012) Central difference particle filter applied to transfer alignment for SINS on missiles. IEEE Trans Aerosp Electron Syst 48(1):375–387

    Google Scholar 

  51. Trimble R7 GNSS and 5700 GPS receivers user guide version 3.64. http://www.trimble.com

  52. Toth CK (2002) Sensor integration in airborn emapping. IEEE Trans Instrum Meas 1(6):1367–1373

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Beijing University of Aeronautics and Astronautics, Beijing, China

    Wei Quan, Xiaolin Gong, Jiancheng Fang & Jianli Li

Authors
  1. Wei Quan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaolin Gong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiancheng Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jianli Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wei Quan .

Rights and permissions

Reprints and permissions

Copyright information

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

About this chapter

Cite this chapter

Quan, W., Gong, X., Fang, J., Li, J. (2015). INS/GNSS Integrated Navigation Method. In: INS/CNS/GNSS Integrated Navigation Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45159-5_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-45159-5_6

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45158-8

  • Online ISBN: 978-3-662-45159-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation