Collaborative Research: Targeting Observations of Tropical Cyclones Using Cooperative Control of Unmanned Aircraft

合作研究：利用无人机协同控制进行热带气旋观测

• 批准号: 0928198
• 负责人: Sharanya Majumdar
• 金额: $ 26.57万
• 依托单位: University of Miami
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0928198&HistoricalAwards=false
• 关键词: Collaborative; Research; Targeting; Observations; Tropical

"This proposal will be awarded using funds made available by the American Recovery and Reinvestment Act of 2009 (Public Law 111-5), and meets the requirements established in Section 2 of the White House Memorandum entitled, Ensuring Responsible Spending of Recovery Act Funds, dated March 20, 2009. I also affirm, as the cognizant Program Officer, that the proposal does not support projects described in Section 1604 of Division A of the Recovery Act." The research objective of this project is to construct an analytical framework to reduce uncertainty in forecasts of hurricane intensity by optimally targeting a coordinated observing network of unmanned aircraft using ensemble-based adaptive sampling and coordination of sampling trajectories. An ensemble-based theory combined with serial adaptive sampling and rapid assimilation updates will be employed for the first time to yield probabilistic flow estimates and optimal sampling configurations. A new theory in decentralized motion coordination will be developed to account for spatially and temporally variable flow fields that exceed the platform speed relative to the flow. The framework will be evaluated using a hierarchy of hurricane models to assess improvements in probabilistic forecasts of the flow. The proposed research will achieve theoretical advances broadly applicable to environmental sampling, including ensemble-based assimilation of near-continuous data, ensemble-based adaptive sampling, and decentralized coordination of unmanned platforms in dynamic flow fields.The broader significance of this research project lies in its potential to improve hurricane forecasts by integrating next-generation weather prediction models with novel strategies for adaptive motion coordination of multiple unmanned aircraft. Better forecasts and reduced uncertainty in hurricane intensity prediction lead to reduced loss of life and property via improved emergency management decisions. Intensity forecasts are dependent on the assimilation of observations of pressure, wind velocity, and temperature at altitudes lower than manned aircraft can safely fly. Small, unmanned aircraft can fill this important gap in observation data by flying at altitudes as low as one hundred meters. A coordinated team of unmanned aircraft can further reduce the uncertainty in intensity forecasts by collecting low-altitude observations in a prescribed spatial distribution. The project will also provide undergraduate and graduate students with a unique training opportunity at the intersection of atmospheric science and dynamical control systems.

“该提案将使用 2009 年《美国复苏和再投资法案》（公法 111-5）提供的资金进行授予，并符合 2009 年 3 月 20 日题为“确保负责任地支出复苏法案资金”的白宫备忘录第 2 节中规定的要求。作为认识到的项目官员，我还确认该提案不支持复苏 A 部门第 1604 节中描述的项目行动吧。”该项目的研究目标是构建一个分析框架，通过使用基于集合的自适应采样和采样轨迹协调来优化无人机协调观测网络，从而减少飓风强度预测的不确定性。将首次采用基于集合的理论与串行自适应采样和快速同化更新相结合来产生概率流估计和最佳采样配置。将开发一种分散运动协调的新理论，以解释相对于流动超过平台速度的空间和时间可变流场。 该框架将使用飓风模型层次结构进行评估，以评估流量概率预测的改进。拟议的研究将取得广泛适用于环境采样的理论进展，包括基于集合的近连续数据同化、基于集合的自适应采样以及动态流场中无人平台的分散协调。该研究项目的更广泛意义在于，它通过将下一代天气预报模型与多个自适应运动协调的新颖策略相结合，有可能改善飓风预报。 无人驾驶飞机。通过改进应急管理决策，更好的预测和减少飓风强度预测的不确定性可以减少生命和财产损失。强度预报取决于对低于有人驾驶飞机安全飞行高度的压力、风速和温度观测的同化。小型无人机可以通过低至一百米的高度飞行来填补观测数据的这一重要空白。协调一致的无人机团队可以通过收集指定空间分布中的低空观测数据来进一步减少强度预测的不确定性。该项目还将为本科生和研究生提供大气科学和动态控制系统交叉领域的独特培训机会。