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.

该小型企业创新研究第一阶段项目的更广泛影响/商业潜力是设计新技术，以使用小型雷达进行恶劣天气监测，以实现准确和快速的天气更新。该技术通过更快的更新速率提高了精度，并且在降低功耗、尺寸和重量方面也具有优势。小型和大型机场可能受益于所提出的雷达处理实现的更高精度的风切变检测现象。这些雷达和相控阵技术具有更好的空间分辨率和更快的更新速度，可以及时向机场工作人员提供有关快速变化的天气状况的信息，并在风暴或其他不利条件影响飞机之前向飞行员发出警告。一些潜在危险和短暂的天气状况，例如机场地区的风切变，可以通过更好的空间分辨率和更快的更新来检测，以警告飞行员避开特定航线。市政当局可以使用这些小型雷达发出恶劣天气警报，并帮助快速评估冰雹损失。通过部署具有数据服务的小型雷达网络，媒体将能够获取实时事件，与公众分享，并获得有关天气现象的更完整的知识。这个小型企业创新研究第一阶段项目将开发并演示多输入多输出（MIMO） ）雷达，可显着增强小型雷达对龙卷风、冰雹和风切变等恶劣天气事件的检测。在第一阶段，算法将在现有的四通道软件定义雷达中开发、模拟和实施。这些算法将首先通过仿真进行评估，以评估性能并优化多个输入和输出参数。优化后的参数将被实施并与使用单输入单输出模式的数据收集进行比较。将利用该团队开发的便携式气象雷达的高级系统雷达参数。将实施优化的 MIMO 参数，并使用便携式气象雷达 (PWR) 或非常相似的原型来以单输入单输出 (SISO) 模式收集数据，并与使用 MIMO 模式收集的数据进行比较。收集到的数据将进行后处理，以量化 MIMO 收集模式的性能优势。在计划的对比和比较性能的过程中，将遇到和分析各种天气类型。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。