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Precise UAV Flight Management Based on Sensor Fusion with Integrity Monitoring

机译:基于传感器融合与完整性监控的精确UAV飞行管理

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摘要

The use of commercial Unmanned Aerial Vehicles (UAVs) has boomed in recent years. This increasing use has brought with significant challenges in respect to UAV flight management, however. As one of the liability-critical applications, UAV flight management requires precise knowledge of the realtime vehicle state in flight, as well as timely alerts to relevant users or entities before a risky event happens, such as intrusion into a no-fly zone. This paper, therefore, presents the user level, accuracy and integrity requirements for unmanned aerial vehicle flight management. We go on then to design a sensor fusion based positioning system to meet the aforementioned requirements. This uses a Kalman filter to integrate Global Positioning System (GPS) data with Inertial Navigation System (INS) data, based on the pseudorange measurements. In addition, an integrity monitoring algorithm is proposed based on a dual-mode fault detector and w test statistics, and real-time dynamic horizontal protection level computation. Onboard experimental results show that the proposed algorithm is capable of delivering the accuracy and integrity requirements for precise UAV flight management.
机译:近年来,使用商业无人机航空公司(无人机)蓬勃发展。然而,这种日益增长的使用带来了对无人机航班管理层的重大挑战。作为责任关键型应用之一,UAV飞行管理需要精确了解飞行中实时车辆状态,以及在风险事件发生的情况下及时警告相关用户或实体,例如入侵到无飞区域。因此,本文介绍了无人机航空公司飞行管理的用户级,准确性和完整性要求。我们继续设计一个基于传感器融合的定位系统,以满足上述要求。这使用卡尔曼滤波器基于伪距测量将全局定位系统(GPS)数据集成到惯性导航系统(INS)数据。此外,基于双模故障检测器和W测试统计,以及实时动态水平保护级别计算,提出了完整性监测算法。板载实验结果表明,该算法能够提供精确的UAV飞行管理的准确性和完整性要求。

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