A vehicular positioning with GPS/IMU using adaptive control of filter noise covariance

Vehicular positioning with GPS/IMU has been studied a lot to increase positioning accuracy. The positioning algorithms mainly use DR (Dead Reckoning) which uses EKF (Extended Kalman Filter). It is basic and very important core technology in positioning section. However, EKF has a major drawback in t...

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Bibliographic Details
Published in:ICT express 2016, 2(1), , pp.41-46
Main Authors: Kim, Juwon, Lee, Sangsun
Format: Article
Language:English
Subjects:
Extended Kalman Filter
GPS
IMU
System/measurement noise covariance
Vehicular positioning
전자/정보통신공학
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Summary:Vehicular positioning with GPS/IMU has been studied a lot to increase positioning accuracy. The positioning algorithms mainly use DR (Dead Reckoning) which uses EKF (Extended Kalman Filter). It is basic and very important core technology in positioning section. However, EKF has a major drawback in that it is impossible to make very accurate system and measurement models for a real environment. In this work, we propose an algorithm to estimate vehicle’s position as distribution form, and to control the system and measurement noise covariance to compensate for this major disadvantage. The proposed method to control noise covariance is independently processed, using fading factor and sensor error while considering the driving condition.
ISSN:2405-9595
2405-9595
DOI:10.1016/j.icte.2016.03.001