ITR - (NHS+ASE) - (dmc+int): Distributed Communications and Control for Multiple Miniature Unmanned Air Vehicles

ITR - (NHS ASE) - (dmc int)：多微型无人机的分布式通信和控制

• 批准号: 0428004
• 负责人: Randal Beard
• 金额: --
• 依托单位: Brigham Young University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0428004&HistoricalAwards=false
• 关键词: ITR; NHS+ASE; dmc+int; Distributed; Communications

Unmanned air vehicles (UAVs) are playing increasingly prominent roles in the nation's defense programs and strategy. There are innumerable uses for such devices in not only military, but civilian, commerical and homeland security applications such as surveillance and reconnaissance, rapid deployment of communication networks, border patrol, sensing hazardous environments, search and rescue, precision agriculture, etc. The focus of this research is on the use of multiple miniature UAVs (MUAVs) for these applications rather than their larger military counterparts such as Predator and Global Hawk. MUAVs have a number of significant advantages over larger platforms, such as their difficulty in being detected or tracked, their ability to more easily avoid threats, to fly at low altitudes and collect more localized data, to be launched without special equipment or a runway, and to spread out and provide a wide ``aperture'' for performing tasks such as geolocation or providing communications links.The benefits of MUAVs do not come without cost, however. There are a number of difficult challenges that must be overcome before their potential can be realized. These challenges include the following: How can a distributed group of MUAVs cooperate and communicate given their constraints on size, power and motion, and in the presence of interference? How are discrepancies in their individual data sets accounted for so that consensus on strategy can be reached? Their mobility is both a blessing and a curse; can the ever-changing shape of an array of MUAV platforms be adequately tracked or maintained for high-resolution localization or imaging tasks? This research effort is devoted to answering questions such as those above.

无人驾驶汽车（UAV）在美国国防计划和战略中扮演着越来越重要的角色。 此类设备不仅在军事中，而且在平民，通讯和国土安全应用中都有无数用途鹰。 MUAVs have a number of significant advantages over larger platforms, such as their difficulty in being detected or tracked, their ability to more easily avoid threats, to fly at low altitudes and collect more localized data, to be launched without special equipment or a runway, and to spread out and provide a wide ``aperture'' for performing tasks such as geolocation or providing communications links.The benefits of MUAVs do not come without cost, however. 在实现其潜力之前，必须克服许多困难的挑战。 这些挑战包括以下内容：鉴于他们对大小，功率和运动的限制以及在存在干扰的情况下，分布式的MUAVS组如何合作和交流？ 他们的个人数据集中的差异如何计算，以便可以达成关于策略的共识？ 他们的流动既是祝福又是诅咒。是否可以对高分辨率本地化或成像任务进行充分跟踪或维护一系列MUAV平台的不断变化的形状？ 这项研究工作致力于回答上述问题。