Research And Simulation Of The Filtering Algorithm In GPS/INS

With the rapid development of modern science and technology, during a long period of research and experiments, people have finally developed an electronic information system which is multidisciplinary cross infiltration and wide use, based on the intelligent vehicle highway systems (IVHS)—Intelligent Transportation Systems (ITS). ITS is a comprehensive transport management system which can play a full role in large scale, multiple ranges, its main principle is:connecting the electronic data communications technology, sensor technology, information processing technology, digital electronic control technology and computer processing technology effective together, and applying them to the transport management information system.During the development of intelligent transportation system, researching on the integrated positioning system has always been a hot issue of high-profile. Currently, the most widely used is the global positioning system (GPS), but in some complex environments, GPS positioning signal system easily lost, it cannot meet the requirements of the users, so it needs the auxiliary positioning system to achieve complementary advantages, finally improved the positioning precision of the whole system. In recent years, because of the superior performance and low cost, the GPS/INS integrated positioning system has been widely used in the sea, land, air field. This paper discussed and analyzed the GPS/INS integrated positioning system, then talked about the basic principle and mathematical model of GPS/INS integrated positioning system, laid the foundation for the following study.In GPS/INS integrated positioning system, the key technology is to act as a two positioning subsystem interface and filter with the function of data fusion, this article focused on the theory of kalman filter in the application of GPS/INS integrated positioning system problems, after doing the simple analysis and discussion, put forward two improved filtering algorithm is applied to GPS/INS integrated positioning system.On one hand, let the improved kalman filter (UKF) algorithm used into the GPS/INS integrated positioning system, a combined kalman filter based on UKF algorithm is constructed, designed the filter and the combination of the positioning system, and then analyzed and set up the GPS/INS integrated positioning system state equation and observation equation. Through the computer simulation analysis, firstly verified the effect of GPS/INS integrated location positioning system was better than the effect of GPS single positioning, followed by a conventional kalman filter, the federal kalman filter based on UKF can effectively reduce the error of GPS/INS integrated positioning system, improved the positioning accuracy of the system.On the other hand, in order to solve the nonlinear problems in GPS/INS integrated positioning system more, a new filtering algorithm is proposed in this paper, interval smoothing UKF algorithm, this algorithm is mainly based on the theory of interval is smooth, on the basis of the UKF algorithm to smooth the estimated system state regulation range, the filter after the data are correct. Interval smoothing UKF algorithm is verified through the simulation can effectively solve nonlinear problems in the system, not only get more accurate state estimates, but also improved the positioning precision of the system.