Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Adaptive two-filter smoothing based on second-order divided difference filter for distributed position and orientation system

Abstract

The distributed position and orientation system (POS) uses transfer alignment to accurately measure multi-node time-spatial reference information, which is necessary for compensating the motion error of imaging sensors used in aerial surveys. Lever-arm deformation in transfer alignment will result in time-varying covariance of measurement noise, which decreases the estimation accuracy. To address this problem, a second-order adaptive divided difference two-filter smoother (ADDTFS) is proposed for transfer alignment. The second-order adaptive divided difference filter (ADDF2) severs as the forward filter to address nonlinearity in the system. The ADDF2 can estimate the measurement noise covariance in real time based on adaptive estimation using innovation information. The weighted statistical linear regression formulation is used in the backward filter to independently estimate the states and error covariance matrices. Then the forward and backward results are combined, to obtain high-precision estimation results in post-processing. Finally, the vehicle experiment results show that the proposed method can improve the attitude precision of transfer alignment in a distributed POS by 27.84%, which has been successfully applied to motion compensation of airborne interferometric synthetic aperture radar (InSAR).

This is a preview of subscription content, log in to check access.

References

  1. 1

    Li L C, Li D J, Pan Z H. Compressed sensing application in interferometric synthetic aperture radar. Sci China Inf Sci, 2017, 60: 102305

  2. 2

    Irwin K, Beaulne D, Braun A, et al. Fusion of SAR, optical imagery and airborne LiDAR for surface water detection. Remote Sens, 2017, 9: 890

  3. 3

    Li J L, Fang J C, Ge S S. Kinetics and design of a mechanically dithered ring laser gyroscope position and orientation system. IEEE Trans Instrum Meas, 2013, 62: 210–220

  4. 4

    Si F, Zhao Y, Lin Y H, et al. A new transfer alignment of airborne weapons based on relative navigation. Measurement, 2018, 122: 27–39

  5. 5

    Ye W, Li J L, Li L C. Design and development of a real-time multi-DSPs and FPGA-based DPOS for InSAR applications. IEEE Senss J, 2018, 18: 3419–3425

  6. 6

    Gong X L, Chen L J, Fang J C, et al. A transfer alignment method for airborne distributed POS with three-dimensional aircraft flexure angles. Sci China Inf Sci, 2018, 61: 092204

  7. 7

    Lü X F, Cheng C Q, Gong J Y, et al. Review of data storage and management technologies for massive remote sensing data. Sci China Technol Sci, 2011, 54: 3220–3232

  8. 8

    Huang Y L, Zhang Y G, Li N, et al. A robust gaussian approximate fixed-interval smoother for nonlinear systems with heavy-tailed process and measurement noises. IEEE Signal Process Lett, 2016, 23: 468–472

  9. 9

    Zhao H, Cui P, Wang W, et al. H fixed-interval smoothing estimation for time-delay systems. IEEE Trans Signal Process, 2013, 61: 316–326

  10. 10

    Gong X L, Zhang J X, Fang J C. A modified nonlinear two-filter smoothing for high-precision airborne integrated GPS and inertial navigation. IEEE Trans Instrum Meas, 2015, 64: 3315–3322

  11. 11

    Liu H, Nassar S, El-Sheimy N. Two-filter smoothing for accurate INS/GPS land-vehicle navigation in urban centers. IEEE Trans Veh Technol, 2010, 59: 4256–4267

  12. 12

    Han S, Kwon W H. A note on two-filter smoothing formulas. IEEE Trans Automat Contr, 2008, 53: 849–854

  13. 13

    Lu Z X, Li J L, Fang J C, et al. Adaptive unscented two-filter smoother applied to transfer alignment for ADPOS. IEEE Senss J, 2018, 18: 3410–3418

  14. 14

    Yu J, Lee J G, Park C G, et al. An off-line navigation of a geometry PIG using a modified nonlinear fixed-interval smoothing filter. Control Eng Practice, 2005, 13: 1403–1411

  15. 15

    Wang X M, He X K, Bao Y, et al. Parameter estimates of Heston stochastic volatility model with MLE and consistent EKF algorithm. Sci China Inf Sci, 2018, 61: 042202

  16. 16

    Malleswaran M, Vaidehi V, Irwin S, et al. IMM-UKF-TFS model-based approach for intelligent navigation. J Nav, 2013, 66: 859–877

  17. 17

    Ning X L, Li Z, Wu W R, et al. Recursive adaptive filter using current innovation for celestial navigation during the Mars approach phase. Sci China Inf Sci, 2017, 60: 032205

  18. 18

    Norgaard M, Poulsen N K, Ravn O. New developments in state estimation for nonlinear systems. Automatica, 2000, 36: 1627–1638

  19. 19

    Karlgaard C D, Shen H. Robust state estimation using desensitized Divided Difference Filter. ISA Trans, 2013, 52: 629–637

  20. 20

    Ghoshal T K, Dey A, Sadhu S, et al. Adaptive divided difference filter for parameter and state estimation of non-linear systems. IET Signal Process, 2015, 9: 369–376

  21. 21

    Ma L F, Wang Z D, Han Q L, et al. Consensus control of stochastic multi-agent systems: a survey. Sci China Inf Sci, 2017, 60: 120201

  22. 22

    Ma L F, Wang Z D, Lam H K, et al. Distributed event-based set-membership filtering for a class of nonlinear systems with sensor saturations over sensor networks. IEEE Trans Cybern, 2017, 47: 3772–3783

  23. 23

    Li J L, Fang J C, Lu Z X, et al. Airborne position and orientation system for aerial remote sensing. Int J Aerospace Eng, 2017, 2017: 1–11

  24. 24

    He X, He W, Qin H, et al. Boundary vibration control for a flexible Timoshenko robotic manipulator. IET Control Theor Appl, 2018, 12: 875–882

Download references

Acknowledgments

The work was supported by National Natural Science Foundation of China (Grant Nos. 61722103, 61571030, 61721091) and in part by International (Regional) Cooperation and Communication Project (Grant No. 61661136007).

Author information

Correspondence to Jianli Li.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Li, J., Zou, S., Gu, B. et al. Adaptive two-filter smoothing based on second-order divided difference filter for distributed position and orientation system. Sci. China Inf. Sci. 62, 192204 (2019). https://doi.org/10.1007/s11432-018-9765-y

Download citation

Keywords

  • distributed POS
  • transfer alignment
  • integrated navigation
  • two-filter smoother
  • divided difference filter