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

在物联网(IoT)、无人机系统(UAS)和5G网络等新兴技术爆炸的刺激下，对无线电频谱空间的需求正在快速增长。不幸的是，有源无线系统的发展往往会增加科学观测中的射频干扰(RFI)。目前，只有很少的射频频谱专门用于科学，而且随着商业应用中对带宽的需求不断增长，可用的少量频谱可能会成为邻近RFI或重新分配用于商业用途的牺牲品。该项目专注于改变遥感方法的范式，开发更高效、更有效的下一代技术和思想，并应对当前和未来的频谱拥堵挑战。特别是，该项目将回收现有的射频通信和导航信号，使这些商业保护频段的新遥感方法能够在精确农业、林业、水资源保护的各种实用解决方案中科学使用。该项目将在实际环境中展示新的、低成本的传感技术，并为农业经济做出贡献。这项开发的技术旨在为全国和世界各地的农业应用带来大量精确灌溉，重点是在经济困难地区和发展中国家。首席调查员(PI)的补充教育目标是让学生、公众和农民更好地了解令人惊叹的微波遥感世界及其对世界上最宝贵的资源--植物和土壤中的水--进行非侵入性追踪的效用。该项目将支持PI通过新的移动应用程序、无人机、游戏和有趣的事实等活动，扩大当今不同学生(包括代表性不足的少数群体)对STEM教育的参与。该项目将建设基础微波遥感科学，一个颠覆性的传感框架，以及非侵入性、可广泛访问和自动化的泛在集成平台，以提高水的利用率。这一目标将通过提供至少三个具体的新贡献来实现：(1)产生在基于UAS的精准农业中向微波频段转变所需的基础知识，(2)设计一个集成/连接的射频试验台来评估新的范式，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湿度反演和田间验证来实现。具体地说，这项工作将通过回收小型无人机微波频谱中的低频辐射，为根区土壤水分观测的准确水监测提供科学基础。探索用于无人机遥感的低频微波频谱是史无前例的，因为现有的小型无人机仪器无法在微波频谱中以如此低的频率进行遥感。该项目将为评估该方法的可行性提供必要的科学基础，并为支持这一范例的算法奠定基础。这项工作对于制定灌溉和旱地农业用水要求以及为基于射频辅助无人机的精准农业新范例创建算法将是重要的。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.