The invention discloses a vehicle
semantic map matching and positioning method and device based on space-based
remote sensing images, and belongs to the field of vehicle autonomous positioning. The method comprises the following steps: firstly, performing multi-scale
cutting on a space-based
remote sensing image to construct an image
pyramid, identifying roads and buildings by using a
deep learning model, and constructing a lightweight
semantic map through vectorization extraction; an upper layer matches a vehicle track with a road center line vector through adaptive sliding window matching, and a track
feature detection function and an
incremental search mechanism are introduced to realize rapid coarse positioning; and the lower layer takes the coarse positioning result as the center, the
laser point cloud is matched with the building contour vector by adopting a simplified ICP
algorithm in the candidate area, only translation is estimated by fixed rotation, and finally, RANSAC conversion is performed once to realize accurate positioning. According to the method, the problem of quick and accurate positioning in a non-cooperative area, a strange scene and a
satellite denial condition is solved.