Research On Information Fusion Method Of Tightly-coupled Integrated Navigation System Based On Kalman Filter

Global position system(GPS) and Inertial navigation system(INS) both have advantages and disadvantages. Since the performance of Integrated navigation system is far excellent than that of subsystem, integrated navigation system is an ideal system to achieve accurate position and navigation data.Kalman filter is a linear optimal estimation method and it has important applications in control theory and engineering. Since the navigation system is a non-linear system, traditional kalman methods no longer meet the system requirements, we need modified kalman algorithm to apply for it. According to data fusion of different depth, integrated navigation system is divided into two types: loosely-coupled and tightly-coupled. GPS and INS are working independently in the loosely-coupled mode(It is a combination of low level),GPS positioning result will be delivered to the INS, which can be used to correct the INS output. This paper studies the GPS/INS tightly-coupled.Firstly, relative technology were discussed in this paper, such as Kalman Filter, GPS and INS, then analyzing the error model of each subsystem of integrated navigation system and completing the modeling of tightly-coupled navigation system. Secondly, an improved UKF algorithm is proposed based on EKF and UKF, the existing nonlinear filter algorithms. Finally, by comparing the performance of tracking a simulation trajectory, we prove that the improved algorithm can be a good deal with nonlinear problems. The algorithm has certain reference to the study of tightly-coupled navigation system.