Research On MEMS-AHRS Attitude Algorithm Under Carrier Maneuvering Conditions

The low-cost AHRS(Attitude and Heading Reference System)system based on MEMS(Micro-Electro-Mechanical System)gyroscope,MEMS accelerometer and electronic magnetometer is an autonomous carrier attitude measurement system.The system has the advantages of low power consumption,small size and low cost,and has broad application prospects in the fields of small aircraft,intelligent robots and human motion analysis.The attitude and attitude system will generate large motion acceleration under the condition of strong maneuverability,which will affect the data output of the accelerometer,resulting in error in the attitude calculation based on acceleration.In addition,the attitude system performs maneuvering in an environment with more magnetic interference,and also generates magnetic interference to the magnetometer,resulting in an error in the attitude calculation based on the magnetic strength information.The above-mentioned errors caused by the motorized motion will cause the accuracy of the attitude result outputted by the attitude and attitude system to be reduced or even unusable.In order to solve the problem of MEMS-AHRS attitude calculation under carrier maneuvering conditions,the main research work of the subject is as follows:Firstly,combined with the characteristics of accelerometer,gyroscope and electronic magnetometer,the error model of the above sensor is established by error analysis,and the calibration of each sensor is completed.Secondly,in view of the maneuvering motion of the carrier in the environment with more magnetic interference,based on the research of the existing attitude solution,the influence of the maneuvering motion of the carrier with magnetic interference on the attitude measurement is analyzed.An attitude system solution that is resistant to maneuvering.It is proposed that the adaptive Kalman filter is used to realize the real-time compensation of the measured values of the sensor,and the Kalman filter correlation error statistic is used to screen the measurement data,and then the gradient descent method is used to perform the pose fusion algorithm.In addition,in order to improve the engineering practicability of the designed algorithm,the traditional Kalman filter mathematical model is designed and optimized,and the structure of the attitude solving algorithm is simplified,which reduces the computational complexity of the algorithm while ensuring that the attitude accuracy does not decrease.The actual engineering implementation of the actual algorithm.Finally,the MPU6050 gyroscope and accelerometer chip,HMC5883 L magnetometer chip and STM32 ARM processor are used to build the hardware platform of MEMS attitude system.At the same time,the maneuverability experiment is designed and the anti-maneuvering ability of the attitude system is tested..In addition,a semi-physical simulation experiment was carried out using the traditional attitude solution algorithm(complementary filter attitude solution algorithm)of low-cost MEMS-AHRS using the host computer as a comparison object.The output attitude accuracy of the attitude solution proposed by this subject is evaluated by comparing the semi-physical simulation results of the traditional algorithm with the output of the designed attitude system hardware platform.The proposed algorithm,complementary filter attitude solution algorithm and attitude reference true value are compared and calculated,and the error statistics of attitude results are obtained.The results show that when the carrier performs strong maneuvering in the environment with high magnetic interference,compared with the traditional complementary filtering attitude solution,the attitude estimation scheme proposed by the subject reduces the roll mean square error by 9%.The mean square error of the pitch angle is reduced by 10%,and the mean square error of the heading angle is reduced by 38%,which effectively improves the accuracy of the attitude and attitude of the attitude and attitude system.