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Research on the Key Technology of the Vehicle Navigation and Positioning

Author: CheLiNa
Tutor: XuAiGong
School: Liaoning Technical University
Course: Figure Cartography and Geographic Information Engineering
Keywords: Integrated Positioning Kalman filter Digital map Map matching Shortest Path
CLC: U463.6
Type: Master's thesis
Year: 2008
Downloads: 75
Quote: 0
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Abstract


Intelligent Transportation Systems ( Intelligent Transportation System , ITS ) is currently the world the forefront of transportation technology , it is a wide range , all-round play the role of real-time , accurate, efficient, intelligent transportation management system . According to statistics, in all subsystems ITS , vehicle management , about 40%. Vehicle management, vehicle navigation and positioning system is the center part of the Intelligent Transportation Systems , is the basis for a variety of other functional applications . This paper studies the some of the key technology in the vehicle navigation and positioning , these key technologies include: (1) vehicle navigation and positioning technology in the analysis comparing the various vehicle navigation and positioning technology , research portfolio positioning technology for vehicle location , portfolio positioning system the error of the sensor , and the establishment of a data processing model based on Kalman filtering . (2) the establishment of navigation digital map and map-matching technology navigable digital map of the functional requirements and standards , research and improved map-matching algorithm . In-depth study for the map-matching algorithm based on DS evidence reasoning , and match the error is relatively large turning sections , parallel sections and special sections overpass sections matching process analysis and given the matching process . (3) the shortest path algorithm in the analysis of Dijkstra's algorithm implementation process as well as its advantages and disadvantages , summed up the optimization algorithm based on Dijkstra's algorithm - priority queue algorithm , searching for the smallest node , greatly reduce the time complexity of the algorithm , has better applicability .

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