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Robust UKF-IMM Filter for Tracking an Off-road Ground Target

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  • Control Theory and Applications
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Abstract

In this paper, the design of a robust UKF-IMM filter for tracking a fulltime off-road ground target is studied and carried out. A detailed description of the target dynamic systems with respect to motion modelling is done for a sharply maneuvering target. A four model IMM filter with two discrete white noise acceleration models and two horizontal coordinated turn models is proposed. In this IMM filter, a low noise and high noise model is proposed for the two pairs of motion models. Low noise model for non-maneuvering or slow maneuvering situations and high noise model for quick and sharp maneuvering situations. The Unscented Kalman filter is used as the base filter due to the highly nonlinear horizontal coordinated turn model with unknown turn rates along with linear Kalman filter for linear systems. Simulation is carried out and results are presented showing the performance of the proposed estimator and demonstrates its capability to perform its designed purpose. The simulated results show that the four model IMM filter can track the highly maneuvering off-road target with acceptable error margin. The error dynamics are observed to be stable with good maneuver detection characteristics. The proposed filter has a low computation complexity and therefore can be adapted to most computers.

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References

  1. T. Kirubarajan, Y. Bar-Shalom, K. R. Pattipati, and I. Kadar, “Ground target tracking with variable structure IMM estimator,” IEEE Trans. on Aerospace and Electronic Systems. vol. 36, no. 1, pp. 26–46. January 2000.

    Article  Google Scholar 

  2. H. S. Son, J. B. Park, and Y. H. Joo, “Segmentalized fcm-based tracking algorithm for zigzag maneuvering target,” International Journal of Control, Automation and Systems. vol. 13, no. 1, pp. 231–237, February 2015.

    Article  Google Scholar 

  3. Y. Bar-Shalom, P. K. Willet, and X. Tian, Tracking and Data Fusion: A Handbook of Algorithms. YBS publishing, Storrs CT, 2011.

    Google Scholar 

  4. X. R. Li and Y. Bar-Shalom, “Design of an interacting multiple model algorithm for air traffic control tracking,” IEEE Trans. on Control Systems Technology. vol. 1, no. 3, pp. 186–194. September 1993.

    Article  Google Scholar 

  5. A. Kraubling and D. Schulz, “Tracking extended targets - a switching algorithm versus the SJPDAF,” Proc. of 9th International Conference on Information Fusion. Florence, Italy, July 2006.

    Google Scholar 

  6. S. Bordonaro, P. Willet, Y. Bar-Shalom, M. Baum, and T. Luginbuhl, “Extracting speed, heading and turn-rate measurements from extended objects using the EM algorithm,” Proc. of IEEE Aerospace Conference. Big Sky, MT, USA, March 2015.

    Google Scholar 

  7. M. Mallick, A. Sinha, and J. Liu, “Enhancements to bearing-only filtering,” Proc. of 20th International Conference on Information Fusion. Xi’an, China, July 2017.

    Google Scholar 

  8. M. Mallick, T. Kirubarajan, and S. Arulampalam, “Comparison of nonlinear filtering algorithms in ground moving target indicator (GMTI) tracking,” Proc. of SPIE. vol. 5204. San Diego, CA, August 2003.

  9. V. B. Frencl, J. B. R. do Val., R. S. Mendes, and Y. C. Zuniga, “Turn rate estimation using range rate measurements for fast maneuvering tracking,” IET Radar, Sonar and Navigation. vol. 11, no. 7, pp. 1099–1107. 2017.

    Article  Google Scholar 

  10. M. Chadli and P. Borne, Multiple Models Approach in Automation: Takagi-Sugeno Fuzzy Systems. J. Wiley & Sons, 2012.

    MATH  Google Scholar 

  11. A. Hocine, M. Chadli, and H. R. Karimi, “A structured filter for Markovian switching systems,” International Journal of Systems Science. vol. 45, no. 7, pp. 1518–1527. 2014.

    Article  MathSciNet  MATH  Google Scholar 

  12. A. Hocine, M. Chadli, D. Maquin, and J. Ragot, “A discrete-time sliding window observer for Markovian switching system: an LMI approach,” Control and Intelligent Systems. vol. 36, no. 2, pp. 174–181, 2008.

    Article  MathSciNet  MATH  Google Scholar 

  13. R. Wang, C. Hu, F. Yan, and M. Chadli, “Composite nonlinear feedback control for path following of four-wheel independently actuated autonomous ground vehicles,” IEEE Trans. on Intelligent Transportation Systems. vol. 17, pp. 2063–2074. 2016.

    Article  Google Scholar 

  14. X. H. Chang, J. H. Park, and P. Shi, “Fuzzy resilient energy-to-peak filtering for continuous-time nonlinear systems,” IEEE Trans. on Fuzzy Systems. vol. 25, pp. 1576–1588. 2017.

    Article  Google Scholar 

  15. X. H. Chang and Y. M. Wang, “Peak-to-peak filtering for networked nonlinear DC motor systems with quantization,” IEEE Trans. on Industrial Informatics. vol. 14, no. 12, pp. 5378–5388. 2018.

    Article  Google Scholar 

  16. H. P. Gao, C. H. Yu, J. W. Choi, and T. I. Seo, “Improvement of tracking performance using prediction - based algorithms for a maneuvering target,” International Journal of Control, Automation and Systems. vol. 9, no. 3, pp. 506–514, June 2011.

    Article  Google Scholar 

  17. C. H. Yu and J. W. Choi, “Interacting multiple model filter-based distributed target tracking algorithm in underwater wireless sensor networks,” International Journal of Control, Automation and Systems. vol. 12, no. 3, pp. 618–627, June 2014.

    Article  Google Scholar 

  18. K. Samuel and J. W. Choi, “Design of a tracking filter suitable for 2D motion dynamics of an off-road target,” Proc. of 17th International Conference on Control, Automation and Systems (ICCAS), Jeju, Korea, October 2017.

    Google Scholar 

  19. X. R. Li and V. P. Jilkov, “Survey of maneuvering target tracking. Part I: dynamic models,” IEEE Trans. on Aerospace and Electronic Systems. vol. 39, no. 4, pp. 1333–1364, October 2003.

    Article  Google Scholar 

  20. L. Mo, X. Song, Y. Zhou, Z. Sun, and Y. Bar-Shalom, “Unbiased converted measurements for tracking,” IEEE Trans on Aerospace and Electronic Systems. vol. 34, pp. 1023–1027, July 1998.

    Article  Google Scholar 

  21. Z. Zhao, X. R. Li, and V. P. Jilkov, “Best linear unbiased filtering with nonlinear measurements for target tracking,” IEEE Trans. on Aerospace and Electronic Systems. vol. 40, no. 4, pp. 1324–1336, October 2004.

    Article  Google Scholar 

  22. L. Jiao, Q. Pan, Y. Liang, and F. Yang, “A nonlinear tracking algorithm with range-rate measurements based on unbiased measurement conversion,” Proc. of 15th International Conference on Information Fusion (FUSION), Singapore, July 2012.

    Google Scholar 

  23. X. R. Li and V. P. Jilkov, “Survey of maneuvering target tracking. Part III: measurement models,” Proc. of the SPIE Conference on Signal and Data Processing of Small Targets, San Diego, CA, USA, pp. 4473–4441, July 2001.

    Google Scholar 

  24. R. E. Kalman, “A new approach to linear filtering and prediction problems,” Trans. of the ASME - Journal of Basic Engineering (Series D). vol. 82, pp. 35–45, 1960.

    Article  Google Scholar 

  25. R. E. Kalman and R. S. Bucy, “New results in linear filtering and prediction theory,” Trans. of the ASME - Journal of Basic Engineering. vol. 83, no. 1, pp. 95–108, March 1961.

    Article  MathSciNet  Google Scholar 

  26. Y. Bar-Shalom, X. R. Li, and T. Kirubarajan, Estimation with Applications to Tracking and Navigation: Algorithms and Software, J. Wiley and Sons, 2001.

    Book  Google Scholar 

  27. D. Simon, Optimal State Estimation - Kalman, H∞, and Nonlinear Approaches, J. Wiley & Sons, Hoboken, New Jersey, USA, 2006.

    Book  Google Scholar 

  28. G. L. Smith, S. F. Schmidt, and L. A. McGee, “Application of statistical filter theory to the optimal estimation of position and velocity on board a circumlunar vehicle,” NASA Technical Report, TR R-135, 1962.

    Google Scholar 

  29. S. Schmidt, “Application of state-space methods to navigation problems,” Advances in Control Systems. vol. 3, pp. 293–340, 1966.

    Article  Google Scholar 

  30. S. J. Julier and J. K. Uhlmann, “A new extension of the Kalman filter to nonlinear systems,” Proc. of AeroSense: The 11th International Symposium on Aerospace/Defense. Sensing, Simulation and Controls, Orlando, Florida, USA, 1997.

    Google Scholar 

  31. S. J. Julier, J. K. Uhlmann, and H. F. Durrant-Whyte, “A new approach for filtering nonlinear systems,” Proc. of the IEEE American Control Conference, Seattle, WA, USA, pp. 1628–1632. June 1995.

    Google Scholar 

  32. S. J. Julier and J. K. Uhlmann, “Unscented filtering and nonlinear estimation,” Proc. of the IEEE. vol. 92, no. 3, March 2004.

    Google Scholar 

  33. H. Q. Zhuang, C. H. Yu, H. P. Gao, J. W. Choi, Y. B. Seo, and T. I. Seo, “Modified-VSIMM algorithm with an application to the naval fire control technology,” International Journal of Control, Automation and Systems. vol. 9, no. 4, pp. 805–813, August 2011.

    Article  Google Scholar 

  34. R. R. Pitre, V. P. Jilkov, and X. R. Li, “A comparative study of multiple-model algorithms for maneuvering target tracking,” Proc. of SPIE. vol. 5809, no. 4, pp. 549–560, May 2005.

    Article  Google Scholar 

  35. X. R. Li and V. P. Jilkov, “Survey of maneuvering target tracking. Part V: multiple model methods,” IEEE Trans. on Aerospace and Electronic Systems. vol. 41, no. 4, pp. 1255–1321, October 2005.

    Article  Google Scholar 

  36. T. H. Fang and J. W. Choi, “Tracking error performance of tracking filters based on IMM for threatening target to naval vessel,” International Journal of Control, Automation and Systems. vol. 5, no. 4, pp. 456–462, August 2007.

    Google Scholar 

  37. B. Panetier, K. Benameur, V. Nimier, and M. Rombaut, “VS-IMM using road map information for a ground target tracking,” Proc. of 7th International Conference on Information Fusion, Philadelphia, PA, USA, July 2005.

    Google Scholar 

  38. B. Panetier, K. Benameur, V. Nimier, and M. Rombaut, “Ground moving target tracking with road constraint,” Proc. of SPIE - The International Society for Optical Engineering, 2004.

    Google Scholar 

  39. R. R. Pitre, V. P. Jilkov, and X. R. Li, “A comparative study of multiple-model algorithms for maneuvering target tracking,” Proc. of the SPIE. vol. 5809. pp. 549–560, May 2005.

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Mechanical Engineering, Pusan National University, Geumjeonggu, Busandaehak-ro 63Beon-gil 2 (Jangjeon-dong), Busan, 46241, Korea

    Jae Weon Choi & Kangwagye Samuel

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  1. Jae Weon Choi
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  2. Kangwagye Samuel
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Correspondence to Jae Weon Choi.

Additional information

Recommended by Associate Editor M. Chadli under the direction of Editor Chan Gook Park. This research was part of the project titled “Development of Eco-friendly Harvester for Manila Clam,” funded by the Ministry of Oceans and Fisheries, Korea.

Jae Weon Choi received his B.S., M.S., and Ph.D. degrees all in control and instrumentation Engineering from Seoul National University, Seoul, Korea, in 1987, 1989, and 1995, respectively. He is currently a Professor in the School of Mechanical Engineering, and has several positions at Pusan National University, Korea including the President of Research Institute of Mechanical Technology, Director of Office for Education Accreditation, and Director of Alliance of BEE Centers. He also had visiting professor positions at M.I.T., Cambridge, MA from August 2003 to August 2004, and at The George Washington University, Washington D.C., from September 2011 for a year. Dr. Choi is a Senior Member of IEEE and AIAA. He is also a member of both IFAC Technical Committee on Linear Systems and Aerospace Committees. He had served from 2003 to 2011 as an Editor for the International Journal of Control, Automation and Systems, and an Associate Editor for over ten years in Conference Editorial Board of IEEE Control Systems Society since 2000. His current research interests include spectral theory for linear time-varying systems, eigen structure assignment for linear time-varying systems with applications to auto pilot design, target tracking filter design, and control and sensor network technologies with applications to aquaculture plants.

Kangwagye Samuel was born in Mbarara, Uganda. He received a master’s degree in mechanical engineering at Pusan National University, Busan, Korea, in 2018. His research focuses on design of guidance, navigation and control systems and the main interests include design of Kalman filters, sensor fusion, estimation theory and control systems design.

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Choi, J.W., Samuel, K. Robust UKF-IMM Filter for Tracking an Off-road Ground Target. Int. J. Control Autom. Syst. 17, 1149–1157 (2019). https://doi.org/10.1007/s12555-018-0249-9

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