Skip to main content
SpringerLink
Log in

Target tracking in standoff jammer using unscented Kalman filter and particle fiter with negative information

  • Published:
Journal of Shanghai Jiaotong University (Science) Aims and scope Submit manuscript

Abstract

To handle the problem of target tracking in the presence of standoff jamming (SOJ), a Gaussian sum unscented Kalman filter (GSUKF) and a Gaussian sum particle filter (GSPF) using negative information (scans or dwells with no measurements) are implemented separately in this paper. The Gaussian sum likelihood which is derived from a sensor model accounting for both the positive and the negative information is used. GSUKF is implemented by fusing the state estimate of two or three UKF filters with proper weights which are explicitly derived in this paper. Other than GSUKF, the Gaussian sum likelihood is directly used in the weight update of the GSPF. Their performances are evaluated by comparison with the Gaussian sum extended Kalman filter (GSEKF) implementation. Simulation results show that GSPF outperforms the other filters in terms of track loss and track accuracy at the cost of large computation complexity. GSUKF and GSEKF have comparable performance; the superiority of one over another is scenario dependent.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Neri F. Introduction to electronic defense systems [M]. Norwood, MA: Artech House, 2001.

    Google Scholar 

  2. Bar-Shalom Y, Blair WD. Multitarget-multisensor tracking: Applications and advances, Vol. III [M]. Boston, MA: Artech House, 2000.

    Google Scholar 

  3. Blair W D, Watson G A, Gentry G L, et al. Benchmark problem for beam pointing control of phased array radar against maneuvering targets in the presence of ECM and false alarms [C]//Proceedings of 1995 American Control Conference. Seattle, USA: IEEE, 1995: 2601–2605.

    Chapter  Google Scholar 

  4. Blair W D, Watson G A, Kirubarajan T, et al. Benchmark for radar allocation and tracking in ECM [J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(4): 1097–1114.

    Article  Google Scholar 

  5. Kirubarajan T, Bar-Shalom Y, Blair W D, et al. IMMPDAF for radar management and tracking benchmark with ECM [J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(4): 1115–1132.

    Article  Google Scholar 

  6. Xu Hai-quan, Wang Guo-hong, Guan Cheng-bin. Tracking technique in the presence of standoff jamming [J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(11): 1353–1358 (in Chinese).

    Google Scholar 

  7. Koch W. On ‘negative’ information in tracking and sensor data fusion: Discussion of selected examples [C]// Proceedings of the Seventh International Conference on Information Fusion. Stockholm, Sweden: IEEE, 2004: 91–98.

    Google Scholar 

  8. Blanding W R, Koch W, Nickel U. Adaptive phased-array tracking in ecm using negative information [J]. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(1): 152–166.

    Article  Google Scholar 

  9. Julier S J, Uhlmann J K. Unscented filtering and nonlinear estimation [J]. Proceedings of the IEEE, 2004, 92(3): 401–422.

    Article  Google Scholar 

  10. Wan EA, van derMerwe R. The unscented Kalman filter for nonlinear estimation [C]// IEEE Symposiums on Adaptive Systems for Signal Processing, Communications, and Control. Lake Louise, Alta, Canada: IEEE, 2000: 153–158.

    Google Scholar 

  11. Gordon N J, Salmond D J, Smith A F M. Novel approach to non-linear/non-gaussian Bayesian state estimation [J]. Proceedings of Institute Electric Engineering, 1993, 140(2): 107–113.

    Google Scholar 

  12. Arulampalam M S, Maskell S, Gordon N, et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking [J]. IEEE Transactions on Signal Processing, 2002, 50(2): 174–188.

    Article  Google Scholar 

  13. Nickel U. Performance analysis of space-time-adaptive monopulse [J]. Signal Processing, 2004, 84(9): 1561–1579.

    Article  MATH  Google Scholar 

  14. Bar-Shalom Y, Li X R, Kirubarajan T. Estimation with applications to tracking and navigation [M]. New York: Wiley, 2001.

    Book  Google Scholar 

  15. Flury T, Shephard N. Bayesian inference based only on simulated likelihood: Particle filter analysis of dynamic economic models [J]. Econometric Theory, 2011, 27(5): 933–956.

    Article  MATH  MathSciNet  Google Scholar 

  16. Gustafsson F. Particle filter theory and practice with positioning applications [J]. IEEE Transactions on Aerospace and Electronic Systems, 2010, 25(7): 53–82.

    Article  Google Scholar 

  17. Ahmed N, Rutten M, Bessell T, et al. Detection and tracking using particle-filter-based wireless sensor networks [J]. IEEE Transactions on Mobile Computing, 2010, 9(9): 1332–1345.

    Article  Google Scholar 

  18. Yap T, Li M, Mourikis A I, et al. A particle filter for monocular vision-aided odometry [C]// IEEE International Conference on Robotics and Automation (ICRA). Shanghai, China: IEEE, 2011: 5663–5669.

    Google Scholar 

  19. Li X R, Jilkov V P. Survey of maneuvering target tracking. Part I: Dynamic models [J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(4): 1333–1364.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Electronic and Information, Northwestern Polytechnical University, Xi’an, 710072, China

    Jing Hou  (侯 静), Zhan-rong Jing  (景占荣) & Yan Yang  (羊 彦)

Authors
  1. Jing Hou  (侯 静)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhan-rong Jing  (景占荣)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yan Yang  (羊 彦)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jing Hou  (侯 静).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hou, J., Jing, Zr. & Yang, Y. Target tracking in standoff jammer using unscented Kalman filter and particle fiter with negative information. J. Shanghai Jiaotong Univ. (Sci.) 19, 181–189 (2014). https://doi.org/10.1007/s12204-014-1488-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12204-014-1488-4

Key words

CLC number

Search

Navigation