Unscented Kalman filter for DR/GPS integrated navigation system

Yongqiang Han*, Jiabin Chen, Zhide Liu, Dunhui Zhao, Chunlei Song, Jingyuan Yin

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

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.

源语言英语
主期刊名Nanotechnology and Computer Engineering
750-755
页数6
DOI
出版状态已出版 - 2010
活动2010 IITA International Conference on Nanotechnology and Computer Engineering, CNCE 2010 - Qingdao, 中国
期限: 20 7月 201021 7月 2010

出版系列

姓名Advanced Materials Research
121-122
ISSN(印刷版)1022-6680

会议

会议2010 IITA International Conference on Nanotechnology and Computer Engineering, CNCE 2010
国家/地区中国
Qingdao
时期20/07/1021/07/10

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