Data Processing And Simulation Of Integrated Navigation Systems

This dissertation studies some general data processing problems that concern integrated navigation systems, and the achievements are widely applicable. As a whole, this paper consists of two main parts: data processing of integrated navigation systems and an introduction of a software platform designed for the simulation and study of integrated navigation systems. The details are as followings:The most usual problems related to navigation data fusion are studied (the local navigation sensors export directly navigation parameters and their accuracies without feedbacks and cross data communications); A novel conservative optimal fusion method of non-feedback multi-source correlated estimators is presented, and this method is extended to the case of more than two data sources; Some new theorems are supplied or proved so that our methods are naturally connected to the achievements up to present, and the integrated theory basis of non-feedback multi-source correlated estimators fusion is founded. At the end of this paper, some useful conclusions are summed up after analyzing and comparing several common-used methods of navigation data fusion.FDI methods are of great importance to integrated navigation. So in this paper, the common FDI methods are summed up, classified and compared in detail; The algorithm of state-consistency-checking provided by Kerr is innovated; Fault diagnosis of the decentralized estimators are thoroughly discussed, for which the diagnosis scenario is also designed.The classic sub-optimal recursive Sage adaptive filter is innovated in this paper. The innovations consist of: synthetically restraining the filter's divergence, as effectively improved the filter's numerical stability; a parallel filter structure is creatively designed to eliminate system biases; and SPRT method is used to control the adjustment of the noise statistics, so as to ameliorate the tracking performance of time-variant noises. Finally, a new sub-optimal recursive Sage adaptive filter is achieved, which is adapt to process high dynamic data.Aiming at the black-box case that local Kalman filters provide only the parameters and covariance matrices of filtered states, a novel multi-model adaptive estimator is designed on the basis of the united CI method. Simulation shows that the new method can properly judge and select the correct local model with quick responses to the changes of local models, so it can be well used as a universal MM estimator.A simulation task of integrated navigation system based on SINS/DB/GPS/GLONASS is introduced in brief, including the designing idea and the simulation models. Also, the integrations of SINS/DB and SINS/DB/GPS/GLONASS are discussed in a nutshell. Then several realizable solutions are designed, as well as each one's characters and disadvantages.