SBIR Phase I: Multiple input multiple output (MIMO) radar processing module for significantly enhanced detection of severe weather and disaster management

SBIR 第一阶段：多输入多输出 (MIMO) 雷达处理模块，可显着增强对恶劣天气和灾害管理的检测

• 批准号: 2313223
• 负责人: Keith Kelly
• 金额: $ 27.5万
• 依托单位: Agile RF Systems LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2313223&HistoricalAwards=false
• 关键词: SBIR; Phase; Multiple; input; multiple

The broader impact/commercial potential of this Small Business Innovation Research Phase I project is to design novel technologies for accurate and fast weather updates for severe weather surveillance using small radars. The technology increases accuracy with faster update rates and also has advantages in terms of decreased power consumption, size, and weight. Small and large airports may benefit from higher accuracy wind shear detection phenomena enabled by the proposed radar processing. Equipped with better spatial resolution and faster updates, these radars and the phased array technology can provide information about rapidly evolving weather conditions in a timely manner to the airport staff and warn the pilots before storms or other adverse conditions affect the planes. Some of the potentially dangerous and short-lived weather conditions, such as wind shear in the airport area, can be detected with better spatial resolution and faster updates to warn the pilots to avoid specific routes. Municipalities can use these small radars for severe weather warnings and aid in rapid assessment of hail damage. By deploying small radar networks with data services, media will have access to real time events to share with the public and gain a more complete knowledge of weather phenomena.This Small Business Innovation Research Phase I project will develop and demonstrate multiple input multiple output (MIMO) radar for significantly enhanced detection of severe weather events such as tornados, hail, and wind shear by small radars. During Phase I, algorithms will be developed, simulated, and implemented in the existing four channel software defined radar. These algorithms will first be evaluated by simulation to assess performance and optimize the multiple input and output parameters. The optimized parameters will be implemented and compared to data collections using the single input single output mode. The high-level system radar parameters of the portable weather radar developed by the team will be utilized. The optimized MIMO parameters will be implemented and the portable weather radar (PWR), or a very similar prototype, will be used to collect data in single input single output (SISO) mode and compared to data collections using the MIMO mode. The collected data will be post processed to quantify performance benefits of the MIMO collection mode. A variety of weather types will be encountered and analyzed during planned efforts to contrast and compare performance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小型企业创新研究阶段I项目的更广泛的影响/商业潜力是设计新型技术，以使用小雷达进行准确，快速的天气更新，以进行恶劣的天气监视。该技术通过更快的更新速度提高了准确性，并且在功耗，大小和体重下降方面也具有优势。小型机场和大型机场可能会受益于提议的雷达加工实现的更高准确性风剪检测现象。这些雷达和分阶段的阵列技术配备了更好的空间分辨率和更快的更新，可以及时向机场工作人员提供有关快速发展的天气状况的信息，并在暴风雨或其他不利条件之前警告飞行员。可以通过更好的空间分辨率来检测到一些潜在危险和短暂的天气状况，例如机场地区的风剪，并更快地警告飞行员以避免特定的路线。市政当局可以使用这些小雷达来进行恶劣的天气警告，并有助于快速评估冰雹损害。通过通过数据服务部署小型雷达网络，媒体将有访问实时事件与公众共享并获得对天气现象的更全面知识。本小型企业创新研究阶段I项目将开发并证明多个输入多重输出（MIMO）雷达，以显着增强对龙卷风，hail，Hail，Hail和Windehear by By Blown gare的严重恶劣天气事件的检测。在第一阶段，将在现有的四个通道软件定义的雷达中开发，模拟和实现算法。这些算法将首先通过模拟评估，以评估性能并优化多个输入和输出参数。将使用单个输入单输出模式将优化的参数与数据收集进行比较。将使用团队开发的便携式天气雷达的高级系统雷达参数。将实现优化的MIMO参数，并将使用便携式天气雷达（PWR）或非常相似的原型，以单个输入单输出（SISO）模式收集数据，并使用MIMO模式与数据收集进行比较。收集的数据将进行后处理以量化MIMO收集模式的性能优势。在计划对比和比较绩效的计划期间，将遇到和分析各种天气类型。该奖项反映了NSF的法定任务，并认为使用基金会的知识分子优点和更广泛的影响审查标准，认为值得通过评估来获得支持。