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Low-Cost Attitude Determination System Using an Extended Kalman Filter Algorithm

机译:使用扩展卡尔曼滤波算法的低成本姿态确定系统

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Attitude determination is one of the most important subsystems in spacecraft, satellite, or scientific balloon missions, since it can be combined with actuators to provide rate stabilization and pointing accuracy for payloads. In this paper, a low-cost attitude determination system with a precision in the order of arc-seconds that uses low-cost commercial sensors is presented including a set of uncorrelated MEMS gyroscopes, two clinometers, and a magnetometer in a hierarchical manner. The faster and less precise sensors are updated by the slower, but more precise ones through an Extended Kalman Filter (EKF)-based data fusion algorithm. A revision of the EKF algorithm fundamentals and its implementation to the current application, are presented along with an analysis of sensors noise. Finally, the results from the data fusion algorithm implementation are discussed in detail.
机译:姿态确定是航天器,卫星或科学气球飞行任务中最重要的子系统之一,因为它可以与执行器结合使用,以提供速率稳定度和有效载荷的指向精度。在本文中,提出了一种低成本的姿态确定系统,该系统使用低成本的商用传感器,精度达到了弧度秒级,该系统包括一组不相关的MEMS陀螺仪,两个倾斜仪和一个磁力仪。通过基于扩展卡尔曼滤波器(EKF)的数据融合算法,速度较慢但精度较差的传感器会更新速度较慢但精度较高的传感器。提出了EKF算法原理的修订版及其在当前应用中的实现,以及对传感器噪声的分析。最后,详细讨论了数据融合算法实现的结果。

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