Paper Title:
Unscented Kalman Filter for DR/GPS Integrated Navigation System
  Abstract

In this paper, unscented Kalman filter (UKF) is studied to estimate the state of Dead reckoning (DR) and GPS integrated navigation system. The positioning error of DR system mainly comes from two factors, the azimuth error and odometer scale factor error. Conventional model of DR/GPS integrated navigation chooses acceleration, position and velocity as observation states, and azimuth error is not estimated, which is one of the key error sources. A new error model of DR/GPS system is adopted that includes azimuth error as a state, which makes it possible to estimate both of the two major error sources. UKF directly approximates the probability density distribution of random variable and avoids the linearization of nonlinear function, which improves the filtering precision. UKF is used to implement an improved DR/GPS system. Road test has been conducted to prove the effectiveness of the scheme.

  Info
Periodical
Advanced Materials Research (Volumes 121-122)
Edited by
Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo
Pages
750-755
DOI
10.4028/www.scientific.net/AMR.121-122.750
Citation
Y. Q. Han, J. B. Chen, Z. D. Liu, D. H. Zhao, C. L. Song, J. Y. Yin, "Unscented Kalman Filter for DR/GPS Integrated Navigation System", Advanced Materials Research, Vols. 121-122, pp. 750-755, 2010
Online since
June 2010
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$32.00
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