The Gps Dynamic Kalman Filtering

Global Position System (GPS) is a precise new-generation positioning system promoted. It has gained extensive development in the fields of military and civilian affairs for its characteristic of all-global,all-weather and high accuracy. In these years, with the development of navigation and orientation, people have higher demands to the orientation precision. It is necessity to improve on the filtering means.Wiener filtering and Kalman filtering are two means of standard filtering. Kalman filtering adapts to the un-stability random process. So ,it gains extensive application.Our aim is to in-depthly study the Kalman filtering. In the paper, firstly, introduce the composition and application of GPS. Then presents the principle of GPS navigation and orientation. At the fourth chapter, the Kalman filtering arithmetic for dynamic GPS is emphases. We carry through lots of simulation and extensive study. In the model of "singer" and "current", we apply the Kalman filtering to simulate and analyze the 8 status and 11 status. Besides, we compare the for-and-aft orientation precision of Kalman filtering. At the base, with how to improve filter's dynamic performance, we advance the improved self-reliant filtering arithmetic and the optimize arithmetic with dissolve factor. simulative results prove that these algorithms are effective to improve the orientation precision. At the end of the paper, we apply the Kalman filtering to GPS/DR and GPS/INS and obtain preferably results.The work in this thesis is a valuable study for amending filtering means and advancing orientation precise of GPS. It will have an aspiring influence on the application of Kalman filtering for the fields of dynamic GPS navigation and orientation.