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An Out-of-sequence Measurement Fusion Method for Guidance Filtering with Delayed Measurements

  • Sang-Hyeon Kim
  • Han-Lim Choi
Regular Paper Control Theory and Applications

Abstract

This paper addresses the problems inherent in the design of a guidance filter with heterogeneous sensor outputs, some of which are subject to a known degree of time delay. The proposed method employs an out-ofsequence measurement fusion scheme in the form of fixed-point Kalman smoothing to effectively incorporate the delayed measurements without needing to significantly alter the underlying nonlinear guidance filtering framework. Two numerical case studies concerning satellite proximity operation and anti-ship missile guidance are presented to demonstrate the effectiveness of the proposed method.

Keywords

Anti-ship missile guidance delayed measurements fixed-point Kalman smoothing out-of-sequence measurement fusion satellite proximity operation 

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References

  1. [1]
    C. J. Harris, A. Bailey, and T. J. Dodd, “Multi-sensor data fusion in defence and aerospace,” The Aeronautical Journal, vol. 102, no. 1015, pp. 229–244, 1998. [click]Google Scholar
  2. [2]
    J. B. Gao and C. J. Harris, “Some remarks on Kalman filters for the multisensor fusion,” Information Fusion, vol. 3, no. 3, pp. 191–201, 2002. [click]CrossRefGoogle Scholar
  3. [3]
    X. Ning and J. Fang, “An autonomous celestial navigation method for LEO satellite based on unscented Kalman filter and information fusion,” Aerospace science and Technology, vol. 11, no. 2, pp. 222–228, 2007.CrossRefzbMATHGoogle Scholar
  4. [4]
    L. Hong, W. Wang, M. Logan, and T. Donohue, “Multiplatform multisensor fusion with adaptive-rate data communication,” Aerospace and Electronic Systems, IEEE Transactions on, vol. 33, no. 1, pp. 274–281, 1997.CrossRefGoogle Scholar
  5. [5]
    B. Ma, S. Lakshmanan, and A. O. Hero, “Simultaneous detection of lane and pavement boundaries using modelbased multisensor fusion,” Intelligent Transportation Systems, IEEE Transactions on, vol. 1, no. 3, pp. 135–147, 2000.CrossRefGoogle Scholar
  6. [6]
    D. E. Maurer, R. W. Schirmer, M. K. Kalandros, and J. S. Peri, “Sensor fusion architectures for ballistic missile defense,” Johns Hopkins APL technical digest, vol. 27, no. 1, pp. 19–31, 2006.Google Scholar
  7. [7]
    R. F. Walter, “Free gyro imaging IR sensor in rolling airframe missile application,” Raytheon Missile Systems, 1999.Google Scholar
  8. [8]
    Y. Bar-Shalom, “Update with out-of-sequence measurements in tracking: exact solution,” IEEE Transactions on Aerospace and Electronic Systems, vol. 38, no. 3, pp. 769–777, 2002.CrossRefGoogle Scholar
  9. [9]
    Y. Bar-Shalom, M. Mallick, H. CHen, and R. Washburn, “One-step solution for the general out-of-sequencemeasurement problem in tracking,” Aerospace Conference Proceedings, vol. 4, 2002.Google Scholar
  10. [10]
    Y. Bar-Shalom, H. Chen, and M. Mallick, “One-step solution for the multistep out-of-sequence-measurement problem in tracking,” IEEE Transactions on Aerospace and Electronic Systems, vol. 40, no. 1, pp. 27–37, 2004.CrossRefGoogle Scholar
  11. [11]
    A. Ray, L. W. Liou, and J. H. Shen, “State Estimation Using Randomly Delayed Measurements,” Journal of Dynamic Systems, Measurement, and Control, vol. 115, no. 1, pp. 19–26, 1993. [click]CrossRefGoogle Scholar
  12. [12]
    S. Challa, R. J. Evans, and X. Wang, “A Bayesian solution and its approximation to out-of-sequence measurement problems,” Information Fusion, vol. 4, no. 3, pp. 185–199, 2003. [click]CrossRefGoogle Scholar
  13. [13]
    S. J. Julier and J. K. Uhlmann, “Fusion of time delayed measurements with uncertain time delays,” Report no., Naval Research Lab. Washington DC Information Technology Div., 2005.Google Scholar
  14. [14]
    I. H. Seo and T. L. Song, “Out-of-sequence-measurement processing for probabilistic multiple hypothesis tracker with measurement reordering,” International Journal of Control, Automation and Systems, vol. 8, no. 2, 2010. [click]Google Scholar
  15. [15]
    H. Zhang, X. Lu, W. Zhang, and W. Wang, “Kalman filtering for linear time-delayed continuous-time systems with stochastic multiplicative noises,” International Journal of Control, Automation and Systems, vol. 5, no. 4, pp. 355–363, 2007.Google Scholar
  16. [16]
    S. Kim, B. Park, H. Choi, and M. Tahk, “Fixed-point smoothing approach for dual-mode guidance filtering with delayed measurement,” AIAA Guidance, Navigation, and Control Conference, 2014.Google Scholar
  17. [17]
    B. D. Anderson and J. B. Moore, Optimal Filtering (Dover Books on Electrical Engineering), Dover Publications, 2005.Google Scholar
  18. [18]
    M. S. Grewal and A. P. Andrews, Kalman Filtering: Theory and Practice Using MATLAB, Wiley-IEEE Press, 2008.CrossRefzbMATHGoogle Scholar
  19. [19]
    R. Hunger, Floating Point Operations in Matrix-Vector Calculus, Munich University of Technology, Inst. for Circuit Theory and Signal Processing 2005.Google Scholar
  20. [20]
    R. Todling, Estimation Theory and Foundations of Atmospheric Data Assimilation, DAO Office Note, 1, 1999.Google Scholar
  21. [21]
    S. Oh, “Multisensor Fusion for Autonomous UAV Navigation Based on the Unscented Kalman Filter with Sequential Measurement Updates,” Proc. of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2010.Google Scholar
  22. [22]
    H. B. Hablani, M. L. Tapper, and D. J. Dana-Bashian, “Guidance and relative navigation for autonomous rendezvous in a circular orbit,” Journal of Guidance, Control and Dynamics, vol. 25, no. 3, pp. 553–562, 2002.CrossRefGoogle Scholar
  23. [23]
    H. Curtis, Orbital Mechanics for engineering students, Butterworth-Heinemann, 2013.Google Scholar
  24. [24]
    J. Lee, Advanced Missile Guidance Laws for Enhancing Survivability, Korea Advanced Institude of Science and Technology, 2006.Google Scholar
  25. [25]
    T. H. Kim, C. H. Lee, and M. J. Tahk, “Time-to-go polynomial guidance with trajectory modulation for observability enhancement,” IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 1, pp. 55–73, 2013.CrossRefGoogle Scholar
  26. [26]
    T. L. Song, S. J. Shin, and H. Cho, “Impact angle control for planar engagements,” Aerospace and Electronic Systems, IEEE Transactions on, vol. 35, no. 4, pp. 1439–1444, 1999.CrossRefGoogle Scholar
  27. [27]
    X. R. Li and Y. P. Jilkov, “Survey of maneuvering target tracking. Part I: Dynamic models,” IEEE Transactions on Aerospace and Electronic Systems, vol. 39, no. 4, pp. 1333–1364, 2003.CrossRefGoogle Scholar

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Aerospace EngineeringKAISTDaejeonKorea

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