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GPS Solutions

, Volume 21, Issue 3, pp 861–872 | Cite as

New optimal smoothing scheme for improving relative and absolute accuracy of tightly coupled GNSS/SINS integration

  • Xiaohong ZhangEmail author
  • Feng Zhu
  • Xianlu Tao
  • Rui Duan
Review Article

Abstract

For mobile surveying and mapping applications, tightly coupled integration of global navigation satellite system (GNSS) and Strap down Inertial Navigation System is usually recommended for direct georeferencing since it can provide position, velocity, and attitude information at higher accuracy and better reliability in a self-contained manner. A post-mission smoothing method is applied to optimally use observation information of both systems and to overcome the shortcomings of Kalman filter in GNSS degraded environments. We propose the revised Rauch–Tung–Streibel Smoother (RTSS) and Forward–Backward combination (FBC) smoothing algorithms for tightly coupled integration. From the analysis and field test, it is found that RTSS smoothing mainly improves the relative accuracy, while FBC mainly contributes to the absolute accuracy. With the complementary characteristics of both smoothing algorithms, an optimal new smoothing scheme combining RTSS with FBC is built. The performance of these three smoothing algorithms is evaluated through a real vehicular test. Compared with RTSS and FBC smoothing algorithms, the new smoothing scheme improves the mean 3D position RMS and the mean 3D attitude RMS by 65.7 and 70%, respectively. It provides better accuracy and smoothness for the position, velocity, and attitude at the same time.

Keywords

Tightly coupled architecture GNSS/SINS integration Rauch–Tung–Streibel Smoother Forward–Backward combination 

Notes

Acknowledegments

The authors gratefully acknowledge two anonymous reviewers for their valuable comments and improvements to this manuscript. This study was supported by the National Key Research and Development Program of China (Grant No. 2016YFB0501803), Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University (Grant No. 15-02-010) and Special Scientific Research Fund for Public Welfare Profession of China (Grant No. 201512002).

References

  1. Chiang KW, Duong TT, Liao JK, Lai YC, Chang CC, Cai JM, Huang SC (2012) On-line smoothing for an integrated navigation system with low-cost MEMS inertial sensors. Sensors 12(12):17372–17389. doi: 10.3390/s121217372 CrossRefGoogle Scholar
  2. Crassidis JL, Junkins JL (2011) Optimal estimation of dynamics systems. CRC Press, Boca Raton, pp 334–337Google Scholar
  3. El-Sheimy N, Hou H, Niu X (2008) Analysis and modeling of inertial sensors using allan variance. IEEE Trans Instrum Meas 57(1):140–149. doi: 10.1109/TIM.2007.908635 CrossRefGoogle Scholar
  4. Elsobeiey M, El-Rabbany A (2014) Efficient between-satellite single-difference precise point positioning model. J Surv Eng 140(2):1009–1016. doi: 10.1061/(ASCE)SU.1943-5428.0000125 CrossRefGoogle Scholar
  5. Godha S, Cannon ME (2005) Integration of DGPS with a low cost MEMS—based Inertial Measurement Unit (IMU) for land vehicle navigation application. In: Proceedings of the ION GNSS 2005, Institute of Navigation, Long Beach, CA, USA, September 13–16, pp. 333–345Google Scholar
  6. Godha S, Cannon ME (2007) GPS/MEMS INS integrated system for navigation in urban areas. GPS Solut 11(3):193–203. doi: 10.1007/s10291-006-0050-8 CrossRefGoogle Scholar
  7. Gong X, Qin T (2013) Airborne earth observation positioning and orientation by SINS/GPS integration using CD RTS smoothing. J Navig 67(2):211–225. doi: 10.1017/S0373463313000623 CrossRefGoogle Scholar
  8. Groves PD (2013) Principles of GNSS, inertial, and multisensor integrated navigation systems. Artech House, Boston, pp 90–92Google Scholar
  9. Hide C, Moore T (2005) GPS and low cost INS integration for positioning in the urban environment. In: Proceedings of the ION GNSS 2005, Institute of Navigation, Long Beach, CA, USA, September 13–16, pp. 1007–1015Google Scholar
  10. Li X, Zhang X, Ren X, Fritsche M, Wickert J, Schuh H (2015) Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo and BeiDou. Sci Rep 5:8328. doi: 10.1038/srep08328 CrossRefGoogle Scholar
  11. Liu H, Nassar S, El-Sheimy N (2010) Two-filter smoothing for accurate INS/GPS land-vehicle navigation in urban centers. IEEE Trans Veh Technol 59(9):4256–4267. doi: 10.1109/TVT.2010.2070850 CrossRefGoogle Scholar
  12. Liu S, Sun F, Zhang L, Li W, Zhu X (2016) Tight integration of ambiguity-fixed PPP and INS: model description and initial results. GPS Solut 20(1):39–49. doi: 10.1007/s10291-015-0464-2 CrossRefGoogle Scholar
  13. Nassar S (2002) Different algorithms for bridging kinematic DGPS outages using SINS/DGPS integration. In: Proceedings of the ION GNSS 2002, Institute of Navigation, Portland, OR, USA, September 24–27, pp. 1474–1482Google Scholar
  14. Nassar S, Niu X, El-Sheimy N (2007) Land-vehicle INS/GPS accurate positioning during GPS signal blockage periods. J Surv Eng 133(3):134–143. doi: 10.1061/(ASCE)0733-9453(2007)133:3(134) CrossRefGoogle Scholar
  15. Rabbou MA, El-Rabbany A (2015) Tightly coupled integration of GPS precise point positioning and MEMS-based inertial systems. GPS Solut 19(4):601–609. doi: 10.1007/s10291-014-0415-3 CrossRefGoogle Scholar
  16. Savage PG (1998) Strapdown inertial navigation integration algorithm design part 1: attitude algorithms. J Guid Control Dyn 21(1):19–28. doi: 10.2514/2.4228 CrossRefGoogle Scholar
  17. Weinbach U, Schön S (2011) GNSS receiver clock modeling when using high-precision oscillators and its impact on PPP. Adv Space Res 47(2):229–238. doi: 10.1016/j.asr.2010.06.031 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Xiaohong Zhang
    • 1
    • 2
    • 3
    Email author
  • Feng Zhu
    • 1
    • 2
    • 3
  • Xianlu Tao
    • 1
  • Rui Duan
    • 1
  1. 1.School of Geodesy and GeomaticsWuhan UniversityWuhanChina
  2. 2.Collaborative Innovation Center for Geospatial TechnologyWuhanChina
  3. 3.Key Laboratory of Geospace Environment and Geodesy, Ministry of EducationWuhan UniversityWuhanChina

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