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Mini-UAV altitude estimation using an inertially stabilized payload

机译:使用惯性稳定有效载荷的微型无人机高度估计

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摘要

A novel method is introduced for autonomous attitude estimation of a mini unmanned aerial vehicle (UAV) carrying an inertially stabilized payload. The method is based on utilizing the outputs of rate gyros normally used to inertially stabilize the payload, and other data that is normally available from conventional aircraft-mounted sensors. A decentralized estimation algorithm is developed, which uses the aircraft/payload mathematical models to bound the estimation errors. Exploiting modern multiprocessor computer technology, the new estimation algorithm comprises two parallel extended Kalman filters (EKFs) and a data fusion algorithm. Real-time experimental tests, incorporating a payload model with real rate gyros mounted on a three-axis flight table, have validated the feasibility of the concept. The theoretical and experimental investigation demonstrates that the estimation algorithm is capable of estimating the attitude angles with an estimation error not exceeding 1 deg, at output rates of 13 Hz, thus constituting a viable substitute for the conventional vertical gyroscope
机译:介绍了一种新颖的方法,用于估计惯性稳定有效载荷的微型无人机(UAV)的自主姿态。该方法基于利用通常用于惯性地稳定有效载荷的速率陀螺仪的​​输出,以及通常可从传统的飞机上安装的传感器获得的其他数据。开发了一种分散估计算法,该算法使用飞机/有效载荷数学模型来限制估计误差。利用现代多处理器计算机技术,新的估计算法包括两个并行扩展卡尔曼滤波器(EKF)和一个数据融合算法。实时实验测试结合了有效载荷模型和安装在三轴飞行平台上的实际速率陀螺仪,已经验证了该概念的可行性。理论和实验研究表明,该估计算法能够以13 Hz的输出速率估计姿态角,且估计误差不超过1度,因此可以替代传统的垂直陀螺仪

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