Integrated Navigation for Autonomous Drone in GPS and GPS-Denied Environments
Integrated Navigation for Autonomous Drone in GPS and GPS-Denied Environments
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GPS 和 GPS 拒绝环境中自主无人机的集成导航
DOI：
10.20965/jrm.2018.p0373
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Satoshi Suzuki
中科院分区：
文献类型：
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作者：
Satoshi Suzuki
在这项研究中，提出了一种新的鲁棒导航系统的无人机在全球定位系统（GPS）和GPS拒绝的环境。一般来说，无人机使用来自GPS的位置和速度信息进行引导和控制。然而，GPS不能在几种环境中使用;例如，GPS在建筑物和树木附近、室内环境中表现出巨大的误差。在这种GPS拒绝的环境中，通常使用基于激光成像检测和测距（LIDAR）传感器的导航系统。但是，LIDAR传感器也有一个弱点，它不能在可以使用GPS的开放室外环境中使用。因此，开发一种在GPS和GPS拒绝环境中无缝操作的集成导航系统是有利的。在这项研究中，使用GPS和激光雷达的无人机的组合导航系统的开发。导航系统的设计基于扩展卡尔曼滤波，并通过数值仿真和实验验证了所开发系统的有效性。
In this study, a novel robust navigation system for a drone in global positioning system (GPS) and GPS-denied environments is proposed. In general, the drone uses position and velocity information from GPS for guidance and control. However, GPS cannot be used in several environments; for example, GPS exhibits huge errors near buildings and trees, indoor environments. In such GPS-denied environments, a Laser Imaging Detection and Ranging (LIDAR) sensor-based navigation system has generally been used. However, the LIDAR sensor also has a weakness, and it cannot be used in an open outdoor environment where GPS can be used. Therefore, it is advantageous to develop an integrated navigation system that operates seamlessly in both GPS and GPS-denied environments. In this study, an integrated navigation system for the drone using GPS and LIDAR was developed. The design of the navigation system is based on the extended Kalman filter, and the effectiveness of the developed system is verified by numerical simulation and experiment.