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논문검색

An Improved Strong Tracking UKF Based on Fading Factor

초록

영어

STUKF (Strong tracking UKF) algorithm uses the time-varying fading factor to fade the past data and reduce the impact on current filter value, thus achieves the goal of adjusting the filter gain matrix in real time. But STUKF algorithm needs three UT for each filtering, and compared with the UKF filter, calculating amount of three UT increases seriously, and it is not conducive to application of engineering, therefore this paper presents an improved STUKF algorithm. Compared with the traditional STUKF filter, this new algorithm introduces the formulas of redefined fading factor. By changing the position of the fading factor, it improves the accuracy and robustness of the algorithm and reduces the computational complexity of the algorithm. Finally simulation results show that the new algorithm has higher precision and stronger robustness.

목차

Abstract
 1. Introduction
 2. Unscented Kalman Filter
  2.1. Problem Description
  2.2. UKF Algorithm
 3. Improved Strong Tracking UKF Algorithm
  3.1. Strong Tracking Filter (STF)
  3.2. STUKF Algorithm
  3.3. ISTUKF Algorithm
 4. GPS/DR Integrated Navigation System Model
 5. Simulation Experiment
 6. Conclusion
 Acknowledgements
 References

저자정보

  • Jian Feng School of Computer and Information Engineering Harbin University of Commerce Harbin, China
  • Xiao-dong Su School of Computer and Information Engineering Harbin University of Commerce Harbin, China
  • Yu-ru Zhang School of Computer and Information Engineering Harbin University of Commerce Harbin, China
  • Hai-tao Jiang School of Computer and Information Engineering Harbin University of Commerce Harbin, China
  • Jun-ling Li School of Computer and Information Engineering Harbin University of Commerce Harbin, China

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