基于MEMS惯性传感器的载波动态姿态估计算法

Xiaodong Geng, Xinan Wang, Guang Luo, Changzheng Huang, Xi Chen, U. Wejinya, G. Shi
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引用次数: 0

摘要

MEMS惯性器件测量精度低,抗干扰能力差。随着时间的推移,MEMS传感器的误差会不断累积,无法长期满足姿态测量的要求。因此,为了提高MEMS传感器姿态测量系统的精度,本文以加速度计和陀螺仪为基本器件,设计了姿态分辨率算法。通过建立载体姿态测量模型,利用加速度计和陀螺仪的输出来设计卡尔曼滤波器。该算法通过加速度计的输出和载体的角速度来更新时间,并通过载体本身的角速度来更新测量值。实验表明,该算法可以抑制MEMS陀螺仪的漂移误差,提高MEMS姿态测量系统的鲁棒性,提高系统精度。
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Carrier Dynamic Attitude Estimation Algorithm Based on MEMS Inertial Sensor
MEMS inertial device has low measurement accuracy and poor anti-interference ability. The error of MEMS sensor accumulates over time, which cannot meet the requirement of attitude measurement for a long time. Therefore, in order to improve the accuracy of the MEMS sensor attitude measurement system, this article uses accelerometers and gyroscopes as the basic devices to design an attitude resolution algorithm. By establishing the carrier attitude measurement model, the output of the accelerometer and gyroscope is used to design the Kalman filter. The algorithm updates the time by the accelerometer output and the angular velocity of the carrier, and updates the measured value by the angular velocity of the carrier itself. Experiments show that the algorithm can suppress the drift error of MEMS gyroscope, improve the robustness of MEMS attitude measurement system, and improve the system accuracy.
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