Performance analysis of vision-based positioning assistance algorithm

Jong Soo Park, Yong Lee, Jay Hyoun Kwon

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Due to recent improvements in computer processing speed and image processing technology, researches are being actively carried out to combine information from camera with existing GNSS (Global Navigation Satellite System) and dead reckoning. In this study, developed a vision-based positioning assistant algorithm to estimate the distance to the object from stereo images. In addition, GNSS/on-board vehicle sensor/vision based positioning algorithm is developed by combining vision based positioning algorithm with existing positioning algorithm. For the performance analysis, the velocity calculated from the actual driving test was used for the navigation solution correction, simulation tests were performed to analyse the effects of velocity precision. As a result of analysis, it is confirmed that about 4% of position accuracy is improved when vision information is added compared to existing GNSS/on-board based positioning algorithm.

Original languageEnglish
Pages (from-to)101-108
Number of pages8
JournalJournal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
Issue number3
StatePublished - 2019


  • Extended kalman filter
  • Machine learning
  • Stereo vision
  • Vehicle positioning


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