Research On Algorithm And Design Of Program In Integrated Navigation System Based On MEMS

Microelectromechanical system(MEMS)devices have achieved rapid development in recent years with the advantages of small size,high reliability,low cost,low power consumption,strong anti-jamming,high sensitivity and resolution,etc.Integrated navigation system formed by Strapdown Inertial Navigation System(SINS)and Global Positioning System(GPS)can play their respective advantages and complement each other,which has become the current hot research topic in the field of navigation.Taking the SINS/GPS integrated navigation system based on MEMS as the research object,this paper focuses on the research of algorithm and program design.Concrete work done as follows:(1)Study on the strapdown inertial navigation algorithm and use C language programming to test the algorithm.Design track generator and take its output as the input of the strapdown inertial navigation algorithm.Compare simulation results with the track generated by track generator to test the correctness of the algorithm.(2)Study on the filtering algorithm of loose coupled integrated navigation system and built the mathematic model of loose coupled integrated navigation system.Based on the model,design Kalman filter to estimate the errors of navigation parameters and inertial devices.Finally use C language programming to implement simulation to validate the algorithm.(3)Study on the filtering algorithm of tightly coupled integrated navigation system and built the mathematic model of tightly coupled integrated navigation system.Based on the model,two kinds of nonlinear filtering algorithm,unscented Kalman filter(UKF)and extended Kalman filters(EKF),are designed to estimate the errors of navigation parameters,inertial devices and GPS.Then simulations are done to test the integrated navigation system which has been designed.(4)Based on measured data of MPU6050 six-axis sensor,AR(1)models of three-axis gyroscopes and three-axis accelerometers are established respectively.Then based on the models,Kalman filters are designed and employed to compensate for random errors.According to the data before and after filtering,Allan variance analysis is used to test the error compensation efficiency in quantitative analysis.(5)Verify the loose coupled integrated navigation algorithm by the practical application.Build a hardware platform taking a TI DSP28335 development as the navigation computer.Based on the platform,the software is designed.Finally the the performance of loose coupled integrated navigation algorithm is tested.