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Research On Integrating Of GPS/DR/MM In Vehicle Navigation System

Posted on:2010-10-06Degree:MasterType:Thesis
Country:ChinaCandidate:L J ZhuFull Text:PDF
GTID:2120330332962318Subject:Geodesy and Survey Engineering
Abstract/Summary:PDF Full Text Request
Vehicle navigation and location systems are the main functions of intelligent transportation systems which one of the key technologies. In recent years, how to make GPS positioning technology and the Dead Reckoning System and a Map-Matching System to better integrate to improve high-precision positioning of vehicles has become an important element of the study vehicle navigation system.This paper first intelligent transportation systems and vehicle navigation and positioning system study of the development history and status at home and abroad were introduced, and then describes the composition of the global positioning system, positioning theory and error, on the impact of vehicle positioning navigation system is relatively large errors analysis focuses on the errors resulting from multi-path effects and propose to weaken the signal to noise ratio by using multi-path error approach, and give an algorithm model.Then, this article describes the Dead Reckoning System, the relevant knowledge, including system components, principle and system error analysis. Then introduced the idea of Map-Matching is given several common matching method is proposed an improved Map-Matching method, and by experiments shows that this method can achieve a higher correct matching rate and reliability. Finally, this paper describes the GPS / DR integrated positioning system proposed positioning system used in combination to improve the federated Kalman filter and gives the filtering algorithms, and the experiments show that application of the federated Kalman filter algorithm can greatly improve the vehicle GPS / DR integrated positioning system for positioning accuracy.
Keywords/Search Tags:Global Positioning System, Dead Reckoning System, Map-Matching, multi-path error, The Federated Kalman Filter
PDF Full Text Request
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