Research On Key Techniques Of Gyro-Free Inertial Measurement Units

Compared with the traditional inertial measurement unit (IMU) with gyros, the gyro-free IMU has the advantages of lower cost, higher reliability and higher shock resistance. Great attentions have been paid to the researches on the gyro-free IMU. The accelerometer configuration, error modeling and analysis, and the algorithm of calculating body motion parameters are the key techniques of gyro-free IMU. These key techniques play an important role in acquiring accurate body motion parameters and in expediting the practical engineering of gyro-free IMU. This dissertation studies the key techniques of gyro-free IMU. The configuration of gyro-free IMU has been designed and analyzed. The errors of the designed configurations have been modeled and analyzed. And state estimation algorithms of gyro-free IMU has been proposed. The main contributions of this dissertation are as follows:The configuration design of gyro-free IMU has been systematically studied. Four different twelve-accelerometer configurations have been designed to solve the problem of error accumulation and singularity. The condition number of configuration matrix has been proposed as an evaluation criterion for different twelve-accelerometer configurations.The two error sources of gyro-free IMU, namely measurement error and configuration error of accelerometers, have been studied. The accelerometer output errors induced by measurement error and by configuration error respectively have been modeled. And the accelerometer output errors induced by measurement error and by configuration error together have also been modeled. The error models are the theoretical foundation of gyro-free IMU error compensation. The influence of stochastic errors of accelerometer outputs on calculation of body motion parameters has been analyzed. The results have demonstrated the effectiveness of the proposed criterion for configuration evaluation.The calculation algorithms of body motion parameters have been studied. Aiming at the proposed four twelve-accelerometer configurations, two different nonlinear Kalman filter, namely extended Kalman filter (EKF) and unscented Kalman filter (UKF), have been designed for body motion parameters estimation. The simulation results indicate that both algorithms correctly estimate the body motion parameters, and reduce the influence of different configurations on estimation. The performance of UKF is slightly better than that of EKF.Configuration D shows the best accuracy on state estimation, which further demonstrates the effectiveness of the proposed criterion for configuration evaluation. In particular, applying UKF to Configuration D and using the consumer-grade accelerometers with the standard deviation of 0.1 m/s2, the accuracy of angular velocity estimation is ±0.4%FS, which is one magnitude higher than the accuracy of consumer-grade gyros. The prototype experiment results furthermore indicate the effectiveness of the two state estimation algorithm. The RMS error performance of angular rate estimation in the prototype experiments is consistent with that of the simulation results.