Pedestrian road detection based on shadow matching

Shadow-matching is a novel technology of global satellite navigation and positioning, which is used to improve positioning accuracy in urban canyon. However, there are some factors affecting the reliability of positioning such as model error, propagation error and algorithm approximation error. This paper present a new scoring method based on optimizing error in algorithm approximation. It can be used to avoid the ambiguity of scoring results and improve the accuracy of positioning. This paper introduces a construction of scoring model and designs an experiment of data acquisition to verify the new scoring model.