TAILIEUCHUNG - Báo cáo "Land-vehicle mems INS/GPS positioning during GPS signal blockage periods "

The demand of vehicle navigation and guidance has been urgent for many years. The idea of integrating multisensor navigation systems was implemented. The most efficient multisensor configuration is the system integrating an inertial navigation system (INS) consisting of MEMS based micro sensors and a global positioning system (GPS). In such system, the GPS is used for providing position and velocity whereas the INS for providing orientation. The estimation of the system errors is performed by a Kalman. | VNU Journal of Science Mathematics - Physics 23 2007 243-251 Land-vehicle mems INS GPS positioning during GPS signal blockage periods T. D. Tana N. T. Longa N. D. Ducb N. P. Thuya Department of Electronics and Telecommunications College of Technology VNU Hanoi 144 Xuan Thuy Cau Giay Hanoi Vietnam bScience Technology Department VNU Hanoi 144 Xuan Thuy Cau Giay Hanoi Vietnam Received 5 November 2007 received in revised form 27 December 2007 Abstract. The demand of vehicle navigation and guidance has been urgent for many years. The idea of integrating multisensor navigation systems was implemented. The most efficient multisensor configuration is the system integrating an inertial navigation system INS consisting of MEMS based micro sensors and a global positioning system GPS . In such system the GPS is used for providing position and velocity whereas the INS for providing orientation. The estimation of the system errors is performed by a Kalman filter KF . A serious problem occurs in the INS GPS system application that is caused by the accidental GPS signal blockages. In this paper the main objective is to improve the accuracy of the obtained navigation parameters during periods of GPS signal outages using different methods. The overall performance of the system have been analyzed by experimentation data and results show that these methods indeed improve the quality of the navigation and guidance systems. 1. Introduction In the last decade the demand for accurate land-vehicle navigation in several applications has grown rapidly 1 . With the strong growth of Micro-Electro-Mechanical-System MEMS technology there appears a new trend in navigation and guidance domain it consists of the integration of INS and GPS altogether 2 . Integrating these two navigation methods can improve the performance of the system and reduce concurrently the disadvantages of both INS and GPS. The Kalman filter KF is utilized to estimate the system errors in order to improve the accuracy

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