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Carrier Dynamic Attitude Estimation Algorithm Based on MEMS Inertial Sensor

机译:基于MEMS惯性传感器的载波动态姿态估计算法

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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.
机译:MEMS惯性装置具有低测量精度和抗干扰能力差。 MEMS传感器的误差随着时间的推移累积,这不能长时间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准确性,本文使用加速度计和陀螺仪作为设计姿态解析算法的基本设备。通过建立载体姿态测量模型,加速度计和陀螺仪的输出用于设计卡尔曼滤波器。该算法通过加速度计输出和载波的角速度更新时间,并通过载体本身的角速度更新测量值。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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