Research On Integrated Navigation Method For MMS Based On GPS/INS

GPS widely used in surveying and navigation based on its significant characteristics, but it won't work when GPS lose satellite signals. INS is a completely autonomous navigation system with the characteristics of strong anti-interference ability and not restricted by the external environment condition. But its accuracy can rapidly decline as the growth of the time. There are a lot of limitations as a single navigation system. The merits and demerits of the GPS and INS make up for each other just right. Therefore, GPS/INS integrated navigation system can avoid their shortcomings and give play to their advantages. So that, the integrated navigation system can improve the performance of the whole navigation system.Kalman filtering theory is a kind of optimal estimation method. It eliminate the random disturbance depending on the measuring system and restore system state again, or recover the original system from the system containing noise according to the measured values. It's essence is reconstruction system's state vector by the measured value.Methods of GPS and INS integrated navigation system can divided into loose combination, close combination and deep combination according to the degree of information exchange. This paper uses the loose combination model. The observed quantity of loose combination mode is the speed and position difference of GPS and INS output, using kalman filter method establish model at the time of data fusion, and then estimate the amount of error. In the end, use the correct value to revise INS output of the position and speed to improve the navigation accuracy. In loose combination mode, the equation of state is the linear error equation of INS and the observation equation is the position and speed difference of the GPS and INS each output. It can be directly applied standard discrete kalman filter algorithm due to the state equation and measurement equation of are linear. Do the optimal estimate for platform attitude error, velocity error, position error and the inertial device error of INS. Then do the feedback correction for INS.In loose combination mode, INS as the main part with satellite navigation aids and the error model is given priority to inertial navigation. Deduce the error model of the accelerometer and gyroscope, the attitude error equation, velocity equations and the position error equation. Analyze the error model and characteristics of SINS under the mobile environment.In the end, do the experimental verification for the integrated navigation system respectively under static and dynamic environment use laboratory existing equipment. Analyze the data of attitude, position, etc. Prove the model's work is simple and easy to realize, and it has high accuracy. The two systems are still keep working independently. Kalman filter has a good applicability in the integrated navigation. The research approach of this paper, the combination model and error model are feasible.