GNSS integration with vision-based navigation for low GNSS visibility conditions

  • Authors:
  • Dae Hee Won;Eunsung Lee;Moonbeom Heo;Sangkyung Sung;Jiyun Lee;Young Jae Lee

  • Affiliations:
  • Konkuk University, Seoul, Korea;Korea Aerospace Research Institute, Daejeon, Korea;Korea Aerospace Research Institute, Daejeon, Korea;Konkuk University, Seoul, Korea;Korea Advanced Institute of Science and Technology, Daejeon, Korea;Konkuk University, Seoul, Korea

  • Venue:
  • GPS Solutions
  • Year:
  • 2014

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Abstract

In urban canyons, buildings and other structures often block the line of sight of visible Global Navigation Satellite System (GNSS) satellites, which makes it difficult to obtain four or more satellites to provide a three-dimensional navigation solution. Previous studies on this operational environment have been conducted based on the assumption that GNSS is not available. However, a limited number of satellites can be used with other sensor measurements, although the number is insufficient to derive a navigation solution. The limited number of GNSS measurements can be integrated with vision-based navigation to correct navigation errors. We propose an integrated navigation system that improves the performance of vision-based navigation by integrating the limited GNSS measurements. An integrated model was designed to apply the GNSS range and range rate to vision-based navigation. The possibility of improved navigation performance was evaluated during an observability analysis based on available satellites. According to the observability analysis, each additional satellite decreased the number of unobservable states by one, while vision-based navigation always has three unobservable states. A computer simulation was conducted to verify the improvement in the navigation performance by analyzing the estimated position, which depended on the number of available satellites; additionally, an experimental test was conducted. The results showed that limited GNSS measurements can improve the positioning performance. Thus, our proposed method is expected to improve the positioning performance in urban canyons.