MRI: Development of a Local Air Traffic Information System (LATIS) for UAS Collision Avoidance Research

MRI：开发用于 UAS 防撞研究的本地空中交通信息系统 (LATIS)

• 批准号: 1727010
• 负责人: Cammy Peterson
• 金额: $ 102.26万
• 依托单位: Brigham Young University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1727010&HistoricalAwards=false
• 关键词: MRI; Development; Local; Air; Traffic

This project, developing a Local Air Traffic Information System (LATIS)--a lightweight, mobile, low-cost, short-range sensor, aims to contribute to avoiding UAS (Unmanned Air System) collisions. Automated sense and avoid (SAA) and other technologies for collision avoidance and coordination of UAS, or drones, are currently an area of major nationwide and worldwide importance and interest. The number of daily UAS flight operations is exploding and will likely outstrip manned aviation by orders of magnitude. To deal with this revolution in usage of U.S. and international airspaces, a major current research area is the development of technologies that enable a UAS Traffic Management (UTM) system that allows safe, efficient low-altitude UAS operations. This project develops LATIS for UAS collision avoidance research. The team aims to develop an instrument that enables research on methods for tracking and controlling many drones in a drone-aware zone.LATIS includes a phased array radar for localized drone tracking, software for sensor processing and drone command and control, and an airborne module which includes an air to ground wireless link and autopilot interface. Current solutions for multi-million dollar air traffic control systems are misaligned to the needs of the smaller, low altitude, and range limited UAS. This project will provide a lightweight, mobile, low cost, short range sensor applicable to this problem set. The phased array radar and connecting ground based system will be capable of identifying and tracking drones that are lost in the ground clutter of current air traffic control systems. The airborne module interfaces each drone with the ground station and phased array radar and includes a custom reconfigurable computing platform suitable for small UAS platforms that will allow future concepts for UAS mesh networks and coordinated control to be tested with the instrument. Users will implement UAS tracking, guidance, communication, and coordination algorithms on the instrument and generate flight test telemetry data that will validate results and guide research in a range of technologies for UAS traffic management. The instrument will be managed by the NSF Industry-University Collaborative Research Center for Unmanned Air Systems (C-UAS), and will allow users within C-UAS and collaborating organizations to expand the capabilities of what may be safely implemented with UAS and delve deeper into research on the intersection where theory and simulation transition to real-world applications.Broader Impacts:With growing commercial interest and market opportunities, high visibility in the media and among the general public, and rapid advances in research in sensors, control algorithms, and novel applications, UAS research is currently in an opportune position. The instrument will be used to test algorithms and answer research questions needed to deploy a future air traffic management system for thousands of drones making package deliveries and a wide range of other commercial services. Significantly, the system will allow researchers to test concepts for the drone traffic system that the National Aeronautics and Space Administration's UAS Traffic Management System consortium, which is closely tied to C-UAS member organizations, is beginning to explore. The instrument comprises lightweight, low power technologies suitable for UAS applications that have only been enabled by the latest digital processing platforms. The risk of key subsystems has been given careful attention.Recently society has witnessed rapid advances in UAS enabling technology. The inability to guarantee safety when flying UAS has greatly hindered the scope and applications for which these vehicles can be used. This technology has the potential to transform the way commercial, scientific, and military industries operate, but can only be realized if the UAS can be safely integrated into national and international airspaces. The LATIS system will allow for the testing and implementation of safe and efficient UAS operations in a local environment and demonstrate a methodology for integration of vehicles into the national airspace. When in operation, the instrument will provide information that will guide future research efforts and inform development of new regulatory frameworks by assisting the Federal Aviation Administration in monitoring and validating technological innovations in UAS tracking, guidance, and control, and will form part of a revolution in the way society interacts with the national airspace.

该项目开发本地空中交通信息系统(LATIS)，这是一种轻便、移动、低成本、近程传感器，旨在为避免无人机(UAS)相撞做出贡献。自动感知和避免(SAA)和其他用于无人机的碰撞避免和协调技术，目前是一个在全国和世界范围内具有重要意义和兴趣的领域。UAS每天的飞行操作数量正在爆炸式增长，很可能会超过载人航空几个数量级。为了应对美国和国际空域使用方面的这场革命，目前的一个主要研究领域是开发能够实现安全、高效的低空无人机操作的UAS交通管理(UTM)系统的技术。该项目开发了用于UAS避碰研究的LATIS。该团队的目标是开发一种仪器，能够研究在无人机感知区跟踪和控制许多无人机的方法。LATIS包括用于本地化无人机跟踪的相控阵雷达，用于传感器处理和无人机命令和控制的软件，以及包括空对地无线链路和自动驾驶接口的机载模块。目前价值数百万美元的空中交通管制系统的解决方案与较小、低空和射程受限的无人机的需求不一致。该项目将提供一种适用于这一问题集的轻便、移动、低成本、短距离的传感器。相控阵雷达和地面连接系统将能够识别和跟踪在当前空中交通管制系统的地面杂波中丢失的无人机。机载模块将每架无人机与地面站和相控阵雷达连接，并包括一个适合小型UAS平台的定制可重新配置计算平台，这将允许使用该仪器测试未来UAS网状网和协调控制的概念。用户将在仪器上实施UAS跟踪、制导、通信和协调算法，并生成飞行测试遥测数据，这些数据将验证结果并指导一系列UAS交通管理技术的研究。该仪器将由NSF工业大学无人机系统协作研究中心(C-UAS)管理，并将允许C-UAS内的用户和协作组织扩展可与UAS安全实施的能力，并更深入地研究理论和模拟过渡到现实世界应用的交叉点。广泛影响：随着商业兴趣和市场机会的增加，媒体和公众中的高能见度，以及传感器、控制算法和新应用研究的快速进展，UAS研究目前处于有利地位。该仪器将用于测试算法，并回答为数千架无人机部署未来空中交通管理系统所需的研究问题，这些无人机正在进行包裹递送和广泛的其他商业服务。值得注意的是，该系统将允许研究人员测试无人机交通系统的概念，美国国家航空航天局的UAS交通管理系统联盟正在开始探索该系统，该联盟与C-UAS成员组织密切相关。该仪器包括轻便、低功耗的技术，适用于仅由最新数字处理平台启用的UAS应用。关键子系统的风险已经得到了仔细的关注。最近，社会见证了无人机使能技术的快速发展。无人机飞行时不能保证安全，极大地阻碍了这些车辆的使用范围和应用。这项技术有可能改变商业、科学和军事行业的运作方式，但只有在无人机能够安全地整合到国家和国际空域的情况下才能实现。LATIS系统将允许在当地环境中测试和实施安全和有效的无人机作业，并展示一种将车辆纳入国家领空的方法。在运行时，该仪器将提供信息，通过协助联邦航空管理局监测和验证无人机跟踪、制导和控制方面的技术创新，指导未来的研究工作，并为新监管框架的发展提供信息，并将成为社会与国家空域互动方式革命的一部分。

项目成果

Networked Radar Systems for Cooperative Tracking of UAVs

用于协作跟踪无人机的网络雷达系统

• DOI: 10.1109/icuas.2019.8797749
• 发表时间: 2019
• 期刊: 2019 International Conference on Unmanned Aircraft Systems (ICUAS
• 作者: Anderson, Brady;Ellingson, Jaron;Eyler, Michael;Buck, David;Peterson, Cameron K.;McLain, Tim;Warnick, Karl F.
• 通讯作者: Warnick, Karl F.

Decentralized UAV Tracking with Networked Radar Systems

使用网络雷达系统进行分散式无人机跟踪

• 发表时间: 2021
• 期刊: 2021 AIAA Scitech Conference
• 作者: Eyler, Michael;Anderson, Brady;Peterson, Cameron K.;McLain, Tim;Warnick, Karl F.
• 通讯作者: Warnick, Karl F.

Uncertainty Velocity Obstacle Avoidance for sUAS Trajectory Planning in a 2D Plane

二维平面中 sUAS 轨迹规划的不确定性速度避障

• DOI: 10.1109/aero47225.2020.9172446
• 发表时间: 2020
• 期刊: 2020 IEEE Aerospace Conference
• 作者: Ellingson, Jaron;Pitts, Emily;Peterson, Cameron K.;Warnick, Karl;McLain, Tim
• 通讯作者: McLain, Tim