Mobile Vehicle Location Estimation Using Pseudolite Landmark and Hybrid Coordinate System Data Fusion Techniques

• Main Authors: Yang-Wen wu, 吳汶洋
• Other Authors: Li-Wei Fong
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/85482497464683832035

碩士 === 育達商業技術學院 === 資訊管理所 === 94 === Abstract Position and velocity errors of Inertial Navigation System (INS) increase unboundedly in time. In order to improve the performance parameters, the alternative of an INS assisted by Global Positioning System (GPS) is frequently adopted. However, GPS still has many unsolved problems existing, for instance the degradation of positioning precision when the view of sky is obstructed. Pseudolite (pseudo-satellite, PL), a ground-based GPS satellite-like signal transmitter, can provide extra measurements in order to improve the positioning precision from GPS alone in the obstructed areas. The pseudolite observations reduced the effect of dilution of precision (DOP) that leads navigation strategy of mobile vehicles. In this research, the pseudolites can be used as landmarks. The problem dealt with here is that of estimating the kinematic state components of a vehicle in autonomous navigation using range, elevation and azimuth angles measured by Line of Sight (LOS) coordinate system. The estimates of the position and velocity of the vehicle are provided by the hybrid coordinate filtering approach (Modified Spherical Coordinates and Cartesian Coordinates Systems). The data fusion algorithm called covariance matching method is employed to reduce the estimation errors. Results of this research show that the Averaged Root Mean Square Error (ARMSE) of position and velocity with the filters was found to be larger (about 87% and 76%) than with the data fusion. Simulation results of proposed algorithm show that the two landmarks may influence the estimating accuracies of mobile vehicle navigation.