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TDoA based UGV Localization using Adaptive Kalman Filter Algorithm

원문정보

초록

영어

The measurement with a signal of time difference of arrival (TDoA) is a widely used technique in source localization. However, this method involves much nonlinear calculation. In this paper, we propose a method that needs less computation for UGV location tracking using extended Kalman filtering based on non linear TDoA measurements. To overcome the inaccurate results due to limited linear approximation, this paper suggests a position estimation algorithm based upon an adaptive fading Kalman filter. The adaptive fading factor enables the estimator to change the error covariance according to the real situation. Through the comparison with other analytical methods, simulation results show that the proposed localization method achieves an improved accuracy even with reduced computational efforts.

목차

Abstract
 1. Introduction
 2. System modeling for UGV localization
  2.1. Analytical methods
  2.2. System modeling
 3. Localization using adaptive fading Kalman filter
 4. Simulation results
 5. Conclusion
 References

저자정보

  • W.J. Sung Sungkyunkwan University
  • S.O. Choi Sungkyunkwan University
  • K.H. You Sungkyunkwan University

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