Collaborative Research: SGER--Unmanned Aircraft System for In-Situ Sensing Along Atmospheric Airmass Boundaries

合作研究：SGER--沿大气气团边界进行原位传感的无人机系统

• 批准号: 0715875
• 负责人: Adam Houston
• 金额: --
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2009-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0715875&HistoricalAwards=false
• 关键词: Collaborative; Research; SGER; Unmanned; Aircraft

A field experiment will be conducted to probe an atmospheric airmass boundary with simultaneous dual-Doppler radars and in-situ sampling with a small Unmanned Vehicle System (UAS). The primary purpose is to develop techniques that will allow the fusing of weather radar data with UAS telemetry to navigate a small unmanned aircraft (UA) to a region of interest that is identified and tracked with weather radar. In addition to the technical challenges, the experiment must also address the evolving Federal Aviation Administration regulations to integrate small UAS into the National Airspace System (NAS). Intellectual Merit: This research activity will demonstrate the ability to navigate a small UA with an atmospheric sensor package into a transient mesoscale atmospheric phenomenon. Data from Colorado State University's NSF-sponsored CHILL and Pawnee radars will be fused with UAS telemetry to navigate the UA to a pre-existing atmospheric airmass boundary where in-situ data will be collected while the UA is controlled from its mobile ground station. This effort leverages technologies and experience developed at the University of Colorado's Research and Engineering Center for Unmanned Vehicles (RECUV). Atmospheric scientists from the University of Nebraska, Lincoln will direct the navigation and interpret the data. Broader Impact: The research program has the potential to add a valuable data acquisition tool for mesoscale dynamic meteorology and potentially provide an instrument that can provide thermodynamic data in regions of severe convective storms that have been difficult to sample. This potentially could lead to better storm forecasts.

将进行一项实地实验，用双多普勒雷达同时探测大气气团边界，并用小型无人驾驶飞行器系统进行现场取样。 主要目的是开发技术，使天气雷达数据与无人机系统遥测数据融合，将小型无人机导航到天气雷达识别和跟踪的感兴趣区域。 除了技术挑战外，该实验还必须解决不断发展的联邦航空管理局法规，以将小型UAS集成到国家空域系统（NAS）中。 智力优势：这项研究活动将展示使用大气传感器包导航小型UA进入瞬时中尺度大气现象的能力。 来自科罗拉多州立大学的NSF赞助的CHILL和Pawnee雷达的数据将与UAS遥测融合，以将UA导航到预先存在的大气气团边界，在那里将收集现场数据，同时UA从其移动的地面站进行控制。 这项工作利用了科罗拉多大学无人驾驶车辆研究和工程中心（RECUV）开发的技术和经验。 来自内布拉斯加大学林肯分校的大气科学家将指导导航并解释数据。 更广泛的影响：该研究计划有可能为中尺度动力气象学增加一个有价值的数据采集工具，并有可能提供一种仪器，可以在难以采样的强对流风暴地区提供热力学数据。 这可能会导致更好的风暴预报。