Development of GNSS/WSS/YRS integration algorithm for land vehicle positioning

Joong hee Han, Jay Hyoun Kwon, Chang Ki Hong, Yong Lee

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Since the Global Navigation Satellite System (GNSS) positioning technique provides precise navigation solutions for a long time, it has been broadly applied for the automotive navigation system. However, the inherent weakness of the GNSS technique is their reliance on the GNSS signal reception environment. To solve this problem, it is necessary to integrate dead reckoning sensors with GNSS positioning technique. Recently, the vehicle dynamic sensors are mounted on the passenger car to improve safety and convenience in driving. Among various vehicle dynamic sensors, wheel speed sensor (WSS) and yaw rate sensor (YRS) can measure the vehicle motion to operate dead reckoning system. In this study, GNSS/WSS/YRS integration algorithm for land vehicle positioning system is developed based on the loosely coupled integration using extended Kalman filter. The performance of the integration algorithm is evaluated based on two test data sets obtained by real test driving by simulating GNSS signal outage. It is found that the proposed algorithm estimates the horizontal positions with meter-level of accuracy when GNSS outage occurs for 30 s. However, the accuracy would be degraded due to irregular road surface so that the study to find additional constraints or integrate with other sensors is necessary in further study.

Original languageEnglish
Pages (from-to)161-172
Number of pages12
JournalSpatial Information Research
Volume25
Issue number2
DOIs
StatePublished - 1 Apr 2017

Keywords

  • Extended Kalman filter (EKF)
  • Global Navigation Satellite System (GNSS)
  • Land vehicle positioning system
  • Wheel speed sensor (WSS)
  • Yaw rate sensor (YRS)

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