Research On Kalman Filtering Method For The Systematic Errors In The GPS Navigation

GPS is widely used in such diverse areas as navigation, surveying, meteorology. Dynamic user applications (especially in the military) with the rapid development of aviation and aerospace industries, the range of GPS applications grows rapidly. GPS Navigation data processing problems are of considerable importance both for the cause of national defense or civil level.In reality, the actual observation vectors and dynamic model often deviates from the assumptions of people, this deviation called model systematic errors, it brings the results of the dynamic navigation bias or filtering results diverge. For the filtering of such deviation, all belong to adaptive filtering. Adaptive filtering can be broken down into function model adaptive filtering and adaptive filtering of the stochastic model, this paper focused on these two methods of error correction from the two aspects of function model and the stochastic model. The contents including:(1) Study the characteristics of the function model systematic errors and their impact on the filtering solution, and programming to achieve the fitting method, including Observing System and the covariance matrix and the model system for the poor and their co-variance matrix fitting methods.(2) Study Sage_husa adaptive filtering methods, and programming to achieve the statistical properties of the system noise and observation noise estimation and correction process.(3) For practical consideration,simplifies these two filtering processes, by putting the fitting function model systematic errors adaptive and Sage_husa adaptive filtering part of the generation into the classic Kalman filter(4) For the characteristics of these two filtering methods, suited to determine the method of fitting the length of the window, introduced a method into the systematic errors of these two correction filter, compared with improved filtering effect of the original filter effects, by analyzing, proved filtering out the introduction of the fitting window length method could bring more accuracy.Thesis focused on the systematic errors on the results of GPS navigation and positioning, given the appropriate correction and compensation methods, improved GPS navigation and positioning capabilities, this paper improved algorithm with the existing algorithms, data simulation and examples solver to verify improvements effectiveness of the algorithm, the algorithm can be used in engineering calculations.