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UKF for the identification of the pico satellite attitude dynamics parameters and the external torques on IMU and magnetometer measurements

机译:UKF用于识别微微卫星姿态动力学参数以及IMU和磁力计测量中的外部扭矩

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In this study, an unscented Kalman filter (UKF) algorithm, which integrates mathematical model of the attitude dynamics with the measurements of inertial measurement unit (IMU) and the magnetometers, is designed. The identified vector is arranged from the Euler angles, angular rates, and the unknown constant components of the external torques (the gravity-gradient, magnetic field pressure and the sun radiation) acting on the pico satellite. Because of the inherent nonlinear dynamics and the nonlinear measurement model caused by the magnetometer measurements, UKF is selected as a filter algorithm. Performance of the proposed algorithm is demonstrated via simulations for a cube pico satellite.
机译:在这项研究中,设计了一种无味卡尔曼滤波器(UKF)算法,该算法将姿态动力学的数学模型与惯性测量单元(IMU)和磁力计的测量集成在一起。从欧拉角,角速度和作用在微微卫星上的外部扭矩(重力梯度,磁场压力和太阳辐射)的未知常数分量中排列识别出的矢量。由于固有的非线性动力学和磁力计测量引起的非线性测量模型,选择UKF作为滤波算法。通过对立方微微卫星的仿真证明了所提出算法的性能。

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