Unmanned Aircraft System Navigation in the Urban Environment: A Systems Analysis

Justin R. Rufa, E. Atkins
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引用次数: 16

Abstract

Unmanned aircraft system navigation in urban environments requires consideration of which combination of sensors can provide the most accurate navigation results in a dynamically changing environment. The traditional Global Positioning System, although useful in open spaces, degrades severely when in urban canyons requiring other complementary sensors to provide position and velocity measurements when necessary. One well-known solution is vision-based sensors that provide measurements through optical flow. Another possibility is the long-term evolution network that is currently used for cellular voice and data transmission as well, as coarse Global-Positioning-System-independent navigation. This paper reviews sensor accuracy and availability as a function of environment characteristics. A simulation framework integrates these different types of sensors to allow for efficient high-level testing of sensor combinations and fusion algorithms. Results show that long-term evolution slightly improves position ac...
城市环境下无人机系统导航:系统分析
城市环境下的无人机系统导航需要考虑在动态变化的环境中,哪种传感器组合能提供最准确的导航结果。传统的全球定位系统,虽然在开放空间有用,但在城市峡谷中,需要其他补充传感器在必要时提供位置和速度测量时,功能严重退化。一个众所周知的解决方案是基于视觉的传感器,它通过光流提供测量。另一种可能性是目前用于蜂窝语音和数据传输的长期进化网络,以及与全球定位系统无关的粗略导航。本文综述了传感器的精度和可用性与环境特性的关系。仿真框架集成了这些不同类型的传感器,以便对传感器组合和融合算法进行高效的高级测试。结果表明,长期进化略微改善了位置。
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