关键词: 智能车辆导航, 复杂环境, 全球卫星导航系统, 双目视觉辅助定位系统

Abstract: The future intelligent vehicle navigation system has to be accurate, steady and reasonably priced. To achieve this goal, many fusion models have been built（GNSS/DR, GNSS/INS, GNSS/MM）. Although some have been proved successfully used in different kinds of environment, they still have shortages, especially in areas where the accuracy of GNSS is jeopardized. This paper researches on a method which can be able to meliorate the GNSS localization precision by stereo-vision utilizing the geographical information of landmarks in partial areas. Random Hough transformation is used to detect landmark, SIFT and K-means algorithm are used to match the landmarks. Stereo-disparity figures out the vector between vehicle and landmark, then it builds an aided model to calculate vehicle’s position. The contents include using experimental vehicle to collect the real-time data in a challenged environment. Finally, after analyzing the error of stereo-vision and the error of GNSS, it proves that the proposed method makes an obvious improvement on GNSS locali-zation results in the areas where landmarks are visible.

Key words: intelligent vehicle navigation, challenged environment, Global Navigation Satellite System（GNSS）, stereo-vision aided localization system