SINS/GPS Tightly Integtation Method Based On CKF

With the progress of the times,higher and higher positioning precision in both navigation and aviation of navigation are demanded.The reliability and precision of a single positioning system can't be effectively guaranteed,All those making integrated navigation arising at this historic moment.Integrated navigation system can maximize play the advantages of each child navigation system,so it can effectively improve the accuracy and reliability of navigation.Compared with the combination of the integrated navigation system,tightly integrated navigation system belongs to a deeper level,it has an effectively-improved positioning precision.In this paper,I mainly research on the strapdown inertial navigation system(SINS)and global positioning system(GPS)integrated navigation system.To solve the problem that the precision measurement of extended kalman filtering(EKF)is low,we use Cubature kalman filter(CKF)method and deduced adaptive Cubature kalman filter(ACKF)method to improve navigation and positioning accuracy.Firstly,three nonlinear filtering methods are detailly researched: the extended kalman filtering,Unscented kalman filter and Cubature kalman filter,and respectively analyzed the advantages and disadvantages of each kind of nonlinear filtering method.Secondly,there goes the coordinate system,working principle,commonly used navigation equation and calculating process of the strapdown inertial navigation system.And in addition,the analysis of the error of strapdown inertial navigation system is completed in this part.Meanwhile the working principle,the basic composition of global positioning system(GPS)and its locating and speed measuring principle are described in details.And then,the basic principle of the error model and error equation of tight SINS/GPS integrated navigation system are analyzed,completing the establishment of the mathematical model of the tight SINS/GPS integrated navigation system.Due to that the system model is nonlinear,the conventional linear kalman filtering method will not be available,so firstly the extended kalman filter is adopted to simulate SINS/GPS integrated navigation system.In order to furtherly improve the navigation and positioning accuracy and solve the problem that the EKF can only be accurate to nonlinear first-order accuracy,the Cubature kalman filter is adopted to simulate tight combination of SINS/GPS system.The simulation results show that CKF can more significantly improve the accuracy of tight SINS/GPS integrated navigation system,when compared with EKF.Finally,in order to solve the problem in the in accuracy of noise statistical properties in tight SINS/GPS integrated navigation system model and to improve the filtering stability and accuracy,I do some research on the classical Sage-Husa algorithm,but it can only be applied in the linear field.Hereto this,I make some study of several adaptive algorithm applicable in the nonlinear field,adaptive extended kalman algorithm,adaptive Unscented kalman algorithm.But the defects of the algorithm itself leads to low filtering precision,so then the thought of nonlinear domain adaptive filtering kalman algorithm is combined with the Cubature kalman filter,the adaptive Cubature kalman filtering algorithm is put forward.And the simulation based on tight SINS/GPS integrated navigation system is completed.The simulation results show that the adaptive Cubature kalman filtering algorithm can improve the navigation and positioning accuracy under the same simulation condition.