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Generally, traditional maps used in navigation are vector maps. This kind of map is rather poor in visual effects, and it’s updated quite slowly, which can not satisfy users’ requirement. This paper puts forward the concept of using remote sensing Images for navigation and does some research on the most critical Image management technology. We describe a new data organization method(Time-Quad-R-Tree) which is fit for the Image navigation. The experiments show that the method can satisfy the up-to-date demand of Image navigation.

Efficient and reliable map-matching algorithms were essential for vehicle navigation systems. Most existing solutions can’t provide trustworthy outputs when the situation was ambiguous (such as at road intersections). Put forward to map matching according to pseudo-Zernike moments. The new Algorithm leads, pseudo-Zernike moments to describe track curve into pseudo-Zernike moments on this foundation of shape, revised a mistake result further. Pass to imitate true and on trial express, the new calculate way has stronger usefulness and credibility under the complicated environment.