论文标题
改进的fasteuler-dlkf小uav ahrs算法
An improved FastEuler-DLKF small-UAV AHRS algorithm
论文作者
论文摘要
准确的态度标题参考系统（AHRS）是无人机可靠飞行系统的重要区别。针对小型UAV接地导航的应用方案，本文建立了陀螺仪/加速度计/磁力计的较松散的夫妇误差模型，并提出了改进的Fasteuler双层Kalman滤波器算法。使用低成本设备，包括MEMS惯性测量单元（IMU）和磁力计，本文构建了无人机的AHRS硬件和软件系统，并设计了离线和实时验证平台。此外，分别通过模拟和飞行测试分析了无人机的态度变化。此外，使用自适应因子来调整测量噪声协方差，以消除加速度计中线性加速度的有害效应，该加速度计解决了滚动和PTICH角。与互补过滤器的实验比较表明，在UAV飞行时，所提出的算法可以提供准确的态度信息，从而提高了态度解决方案的准确性和可靠性，并消除了对态度估计的陀螺仪偏置的影响。
The accurate Attitude Heading Reference System(AHRS) is an important apart of the UAV reliable flight system. Aiming at the application scenarios of near ground navigation of small-UAV, this paper establishes a loose couple error model of the gyroscope/accelerometer/magnetometer, and presents an improved FastEuler Double-Layer Kalman Filter algorithm. Using low-cost devices which include MEMS Inertial Measurement Units(IMU) and magnetometers, this paper constructs the AHRS hardware and software systems of UAV, and designs the offline and real-time verification platforms. Moreover, the attitude changes of UAV is analyzed by the simulation and flight test, respectively. In addition, an adaptive factor is used to adjust the measurement noise covariance in order to eliminate the harmful effects of linear acceleration in the accelerometer, which is solved the roll and ptich angle. The experimental comparison with the Complementary Filter shows that the proposed algorithm can provide accurate attitude information when UAV is flying, which improves the accuracy and reliability of attitude solution, and removes the influence the gyro bias for the attitude estimation.
