Design And Implementation On GPS/BD-2Satellite Positioning Algorithm

Global Positioning System is a new generation of sophisticated satellite navigationand positioning system. As the typical of this system, GPS has a global, all-weather,continuous real-time three-dimensional precision navigation and positioning capabilities.Then the observation point location has been an important research and application fieldsin the positioning systems. This thesis, which mainly on the method through observationpoint positioning to implement satellite positioning by software.In this thesis, firstly, the process of dynamic navigation data has been reverted andanalyzed. Secondly, it chose the pseudo-range algorithm which is most universal in thearea of navigation algorithm to analysis, improvement and implementation. Discussed thenecessity to build a reliable function model, and modeled it which according to the processof positioning. This thesis proposed a new satellite selection algorithm which aimed atmodifying elevation threshold according to the environment, better positioned to avoidinvalid frequently encountered in the real situation of star selection, proved the efficiencyand improved the positioning adoption accuracy. In positioning module, it mainly uses theleast squares method, and combined with Kalman filter algorithm to estimate the error. Inthe part of implementation, data is obtained from the IGS where provided satelliteephemeris and the real station pseudo-range information strictly in present time, so thecalculation made on the basis of the result is reliable and realistic significance. Finally, itdisplayed the results of GPS satellite positioning correctly and proved the algorithm whichmet the demands of positioning requirements after the estimates of error by program.Because of the date which GPS received belongs to WGS-84coordinate system, andthe results of the positioning which displayed in local coordinate system, so it is necessaryto transform by given the modeling of coordinate transformation. It was implemented byVC++during all the steps of transformation and data processing. By using MATLAB, notonly verified the basis to delimit the threshold of elevation, but also optimized theestimates of error through Kalman filter algorithm.