Adaptive Fusion Navigation Theory And Methods And Their Applications, Gps And Ins

This dissertation mainly; focuses on the theories and algrithms of GPS and INS kinematic data processing and integrated navigation data fusion. The main works and contributions are summarized as follows:1. The key problems in GPS navigation and positioning are analyzed based on the kinematic model of the vehicle movements. It is shown, by calculations and analysis, that selecting the reasonable functional models and stochastic models in kinematic positioning is necessary.2. The principle of fading filtering is introduced and discussed, then the adaptively robust Kalman filtering and fading filtering is synthetically compared. The shortcomings of the fading filtering are analyzed. Finally, an adaptively robust Kalman filtering arithmetic based on the current statistical model is presented.3. The influences of adaptive factors on navigation results is analyzed and discussed in detail. Three kinds of adaptive factors based on discrepancy between the geometrical positions and the kinematic model predicts and a variance component ratio between model predicts and observations are described. It is shown, by comparison and analysis, that all of the four adaptive factors can control the influences of the vehicle disturbances in movements on the navigation results. The results derived by the adaptive factor constructed by the variance component ratio are slightly better than those derived by other adaptive factors.4. The shortcomings of federated filtering are presented and synthetically analyzed in detail The adaptively robust federated filtering based on the theory of robust estimation and variar component estimation is put forward.5. Firstly SINS navigation results are calculated based on the simulated data. Then th< adaptive filtering is applied in IMU/GPS integrated navigation system, in which the adaptivi factor is replaced by the fading factor. A practical example is given. The results prove that th> adaptive filtering combined with the fading factor is valid and reliable when applied i: IMU/GPS integrated navigation system.6. The study and analysis of adaptively integrated navigation system based on robus estimation outputs and variance component estimates of multi-sensor measurements an adaptive integrated navigation of multi-sensor adjustment outputs prove that the adaptively dai fusion algorithms are with high reliabal, high degree of fault tolerance and are practical for re; time distribute navigation system application.On the basis of adaptively integrated navigation of multi-sensor adjustment outputs, a adaptively integrated navigation of multi-sensor adjustment outputs with colored noise is p forward. By fitting and predicting of the colored noise of the kinematic states, it shows, by tJ calculation and analysis with simulated date, that the new algorithm will give the more actuand reliable parameter estimates of the integrated navigation system.