Influence And Control Of Dynamic Navigation Colored Noise

The estimation theory and methods on colored noises in kinematic navigation and positioning are systematically discussed in this dissertation. At first, this paper briefly introduces the background and significance of research on estimation theory of colored noises. The influence function (IF) ot the colored noises on the kinematic positioning is derived and analysed. The characteristics of two classical solutions of colored noises are also presented here. The sources of the colored noises are analyzed in the kinematic GPS navigation and positioning. In order to judge whether the colored noises exist or not and verify whether the model meet the need in fact or not, we discussed the statistic testing, too. Then, Sage adaptive filtering usually used in kinematic GPS navigation and positioning and its shorcoming are analyzed. The weights of measurement residuals and state correction residuals are modified according to the self-correlation property of colored noise and robust estimation. The procedure of weighted prediction of covariace matrix not only resists the influence of outlying kinematic model errors, but also controls the effects of measurement outliers. Finally, in allusion to the shortcomings on the fitting of colored noises by least square, a new procedure is presented to modify the estimations of model parameter of the colored noises. It can control the effects of the correlation noise of exept for first order self-correlation noise. Theoretical analysis and test results show that two modified procedures improve the precision and adaptability of Kalman filtering effectively.