Earticle

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

키워드

저자

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

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605