微小型航姿测量系统及其数据融合方法

摘要

以小型无人机航姿测量系统的微小型化为背景,利用MEMS惯性测量元件研制了一种低成本微型航姿测量系统.针对MEMS器件用于载体航姿测量时精度低、易发散的问题,提出一种计算量小、实时性强的加速度信息、磁场强度信息、陀螺信息的融合方法.采用卡尔曼滤波器对系统的俯仰角、滚转角和航向角的误差进行最优估计；设计数据融合的判别准则,并根据判据的判断结果调整卡尔曼滤波器中的量测信息,使系统可用于小型无人机的定高自主飞行.实验结果表明,系统输出航姿的更新频率可达100Hz,航姿测量误差小于0.6°,航姿标准差小于0.09°；将其应用于某小型固定翼飞行器的飞行控制系统中进行自主飞行实验,完成了预定的飞行任务.%Attitude and heading information is very important for micro-unmanned air vehicle(MUAV). In this paper, a low-cost micro attitude and heading measurement system is designed using MEMS inertial sensors. To overcome shortcomings such as low precision and easy divergence, a data fusion method with the reduced computational complexity is designed, by which the information from accelerometers, magnetometers and gyroscopes is fused. The pitch angle error, roll angle error and yaw angle error of the system are estimated with Kalman filter. Criterions of data fusion are provided to adjust the measurement information in the Kalman filter equations so that the system can be used while the MUAV is flying in invariable height. Experiment results show that the system can update the parameters of attitude and heading at the rate of 100 Hz, the measurement error is less than 0.6°, and the standard deviation of attitude and heading measurements is less than 0.09°. Moreover, the autonomous flying tests on a fixed wing aircraft by using the system successfully finish the predetermined flight mission.