CAREER: Recycling the Radio Spectrum for Science: A New Paradigm for UAS-based Precision Agriculture

由于物联网（IoT）、无人驾驶飞机系统（UASs）和5G网络等新兴技术的爆炸式增长，对无线电频谱空间的需求正在迅速增长。不幸的是，有源无线系统的发展往往增加了科学观测中的射频干扰（RFI）。就目前而言，很少有射频频谱专门用于科学，而少量可用频谱可能成为邻近RFI的牺牲品，或者在商业应用中对带宽需求不断增长之后重新分配用于商业用途。该项目的重点是改变遥感方法的范式，开发更高效、更有效的下一代技术和理念，并应对当前和未来频谱拥堵的挑战。特别是，该项目将回收现有的射频通信和导航信号，使这些商业保护波段的新遥感方法能够用于精准农业，林业和水资源保护的无数实际解决方案的科学用途。该项目将在实际环境中展示新的低成本传感技术，并为农业经济作出贡献。开发的技术旨在为国内和世界范围内的农业应用引入一系列精确灌溉，重点是经济困难地区和发展中国家。首席研究员（PI）的补充教育目标是提高学生、公众和农民对微波遥感的惊人世界的认识和理解，以及它在非侵入式跟踪世界上最宝贵的资源：植物和土壤中的水方面的应用。该项目将支持PI的努力，通过新的移动应用程序、无人机、游戏和有趣的事实等活动，扩大当今多元化学生（包括代表性不足的少数群体）对STEM教育的参与。本项目将构建微波遥感基础科学、颠覆性遥感框架和无侵入性、可及性、自动化的集成泛在平台，以提高水资源利用水平。这一目标将通过提供至少三个具体的新贡献来实现：(1)产生向基于无人机的精准农业的微波频段范式转变所需的基础知识，(2)设计用于评估新范式的集成/连接RF测试平台，以及(3)将智能手机集成到低成本无人机中以进行更广泛的适应。这些目标将通过进行先进的电磁建模和模拟、基于物理感知的机器学习的土壤水分检索和现场验证来实现。具体来说，这项工作将通过回收小型无人机的微波频谱低频辐射，为根区土壤水分观测的精确水分监测提供科学依据。利用无人机进行低频微波频谱的遥感探测是前所未有的，因为目前还没有小型无人机仪器能够在如此低的微波频谱上进行遥感。该项目将为评估该方法的可行性提供必要的科学依据，并为支持这种范式的算法奠定基础。这项工作对于制定灌溉和雨养农业的用水要求以及为射频辅助的基于无人机的精准农业的新范式创建算法将非常重要。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Demand for radio spectrum space is growing quickly, spurred by the explosion of emerging technologies such as the Internet of Things (IoT), Unmanned Aircraft Systems (UASs), and 5G networks. Unfortunately, the growth of active wireless systems often increases radio frequency (RF) interference (RFI) in science observations. As it stands, very little of the RF spectrum is dedicated to science, and the small amount of spectrum available can fall victim to neighboring RFI or re-allocation for commercial use in the wake of the growing demand for bandwidth in commercial applications. This project focuses on changing the paradigm of remote sensing methods and developing next generation technologies and ideas that are more spectrum efficient, more effective, and meet the challenges of present and future spectrum congestion. In particular, the project will recycle existing RF communication and navigation signals to enable new remote sensing methodologies at these commercially protected bands for scientific use in a myriad of practical solutions for precision agriculture, forestry, water conservation. This project will demonstrate new, low-cost sensing technologies in practical settings and contribute to the agriculture economy. The developed technology aims to usher in a host of precision irrigation for agricultural applications in the nation and worldwide with emphasis in economically distressed areas and developing countries. The complementary educational goals of the Principal Investigator (PI) are to generate a greater awareness and understanding among students, the public, and farmers about the amazing world of microwave remote sensing and its utility for non-intrusive tracking of the world’s most precious resource: water in plants and soil. The project will support the PI’s efforts to broaden the participation of today’s diverse students, including underrepresented minority groups, in STEM education though activities such as new mobile apps, drones, games, and fun facts. This project will construct fundamental microwave remote sensing science, a disruptive sensing framework, and integrated ubiquitous platforms that are non-intrusive, widely accessible, and automated to improve water utilization. This goal will be realized by offering at least three specific new contributions: (1) generating fundamental knowledge needed for a paradigm shift towards microwave bands in UAS-based precision agriculture, (2) designing an integrated/connected RF testbed for evaluating the new paradigm, and (3) integrating smartphones into low-cost drones for broader adaptation. These objectives will be achieved by conducting advanced electromagnetic modeling and simulations, physics-aware machine-learning-based soil moisture retrievals, and field validation. Specifically, this work will generate the scientific basis for accurate water monitoring of root-zone soil moisture observations by recycling low-frequency emissions in microwave spectrum from small drones. Exploring the low-frequency microwave spectrum for remote sensing from drones is unprecedented because no existing small drone instrument is capable of remote sensing at such low frequencies in microwave spectrum. This project will fill in the necessary scientific basis to evaluate the approach’s feasibility and develop the foundation for the algorithms to support such a paradigm. This work will be important for developing the requirements for water utilization in irrigated and rainfed farming and creating algorithms for the new paradigm of RF-assisted UAS-based precision agriculture.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.