Research On Integrated Navigation System And Filtering Algorithm

Integrated navigation system has been widely used in the human aviation, aerospace and other areas currently. The study on the integrated navigation System based on Inertial Navigation System (INS) and Global Positioning System (GPS) is done in this paper.In the paper, inertial navigation systems and global satellite positioning systems are explored in detail, their working principle, system components, error sources and model calculations are both discussed here. The rapid development of computer technology has promoted the development of Kalman filtering technique and the development of Kalman filtering has an important meaning to the development of integrated navigation system. The require of the kinematic model of the system is higher in the practical application of conventional Kalman filtering technique, this requirement is difficult to be guaranteed in general, making the system can not be the optimal filter estimate may even lead to filter divergence.In this paper, conventional Kalman filter in practical applications its shortcomings, as discussed in a number of other improved filtering techniques such as Extended Kalman filtering, Unscented Kalman filtering, Sage-Husa adaptive filtering, robust filtering. A simple simulation of the performance of the extended Kalman filter and the unscented Kalman filter is done in the nonlinear case in this article.Error model is established on the INS/GPS integrated navigation system. Different filtering algorithms based on simulation results are done by using the mode of position/speed combination. The simulation results show that for INS/GPS integrated navigation system, improved filtering algorithm for filtering accuracy and reliability compared to conventional Kalman filter performance even better.