Parametric Identification And Error Compensation Of MEMS Inertial Sensors And IMU

Due to the advantages of MEMS inertial sensor, such as low cost, small size, high reliability, large measurement range and easy to digitations, the navigation technology using MEMS inertial sensors has been developed rapidly and widely used in such field as auto industry, biomedicine, aerospace, precision instruments, national defense, etc.However, MEMS inertial sensors have shortcomings like low measurement precision and high noise that need to be overcome. Besides optimizing the mechanism structure, enhancing the circuit performance and shielding external electromagnetic disturbance, another effective approach to fabricate moderate accuracy system with low precision inertial instrument is to analyze, modeling and filter the information of MEMS inertial sensors, to exploit new high calibration method, and to fuse information with alike or unlike sensors.To achieve the purpose what has been discussed above, the dissertation includes several works as follows:Contrive a great deal experiments to analyze the signals of gyros and accelerators in MIMU thoroughly. Those analyses method are spectrum analysis, autocorrelation function analysis, PSD analysis, Allan variance and wavelet analysis, and so forth. The results of experiments were used to know the performance index detail and then estimate the limit navigation precision of MEMS INS on the one hand. On the other hand, the noise statistics of gyros and accelerators provide gist for the parameter design of Kalman filter later, and so help avoiding emanation of Kalman filter due to the inaccurate statistics of model and observation noise."Virtual Gyro" technology was presented to improve the sensor performance. The "Virtual Gyro", which has the same meaning with the JPL lab, was realized by using three MEMS gyros on each measure axes to get the same angular velocity and fusing the information by information fusion technology. This paper brings forward the implementation detail of "Virtual Gyro" technology after introducing its principle. Through simulating gyro signal under situations of awfully small, small and large relativity, the correctness of virtual gyro Kalman filter was validated. And then, practical gyro signals of MIMU was collected and processed. The experiment result shows that virtual improve the whole precision by about 1.9 times minimum and 2.7 time maximum. Besides, the dissertation put forward three methods to improve the relativity of gyro signal.Discussed high precision calibration means when there exists large misalignment in MIMU. This method includes two levels and two steps: component level calibration and MIMU level calibration. Component calibration analyzes the measurement error reason of MEMS inertial components according to the principle of gyro and accelerator first. And design Kalman filter to estimate the error index. In this level, the practical effect of Kalman filter was not as effective as simulation. The reason for this instance was due to the inaccuracy of model. In the end, advanced Kalman filter which absorbed process virtual noise had an excellent performance. MIMU calibration was a must because of the non-orthogonal angle and turntable installation error. An precision measurement model of MIMU was built first based on reasonable hypothesis for one thing and seeking parameters with restriction using least square method for another thing. The first step of calibration is coarse calibration using conventional method. In this step, three axis point to sky and ground for once separately and compute the coarse value of non-orthogonal angle. The second step is to design an optimal experiment project according the D-optimal principle for MIMU precision measurement model.Established dynamic error model and identified the coefficients to improve navigation system precision. Through testing method to establish the dynamic error measurement model, then parameter identification to calibration for MIMU and a mass of experiments to validate the model finally, the effectiveness of model and error compensation were proved.Cut down the influence of temperature on the inertial instruments. The influence of temperature on inertial instruments precision mainly related to environment temperature, temperature variation rate and temperature gradient, this paper develop compensation model due to the difficulty of mechanism model and put forward an advanced calibration method in whole temperature range to solve the defect of conventional temperature error calibration. This method takes component temperature, temperature variation rate, environment temperature and its rate, and output voltage for input, and takes angular velocity and accelerator measurement for output. It uses stepwise regression analysis to get optimized segment error compensation model. Significance analysis and experiment show that this advanced method cut down the influence of temperature variance to MIMU.Discussed integration navigation of MEMS INS and EC. From the angle of combination model, an optimized observation was designed to combine the output of gyros, accelerators, tilt sensor and magnetic compass, and so on. This integration can get relatively precision estimation of inclination and heading angle as well as the constant drift of three gyros.