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

职业：科学回收无线电频谱：基于 UAS 的精准农业的新范式

• 批准号: 2142218
• 负责人: Mehmet Kurum
• 金额: $ 50万
• 依托单位: Mississippi State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2142218&HistoricalAwards=false
• 关键词: CAREER; Recycling; Radio; Spectrum; Science

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.

在物联网（IoT）、无人机系统（UAS）和5G网络等新兴技术爆炸式发展的推动下，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会增加科学观测中的射频（RF）干扰（RFI）。目前，只有很少的RF频谱专用于科学，并且随着商业应用对带宽需求的不断增长，少量可用频谱可能成为邻近RFI或重新分配用于商业用途的牺牲品。 该项目的重点是改变遥感方法的范式，开发下一代技术和思想，这些技术和思想具有更高的频谱效率，更有效，并满足当前和未来频谱拥塞的挑战。 特别是，该项目将回收现有的射频通信和导航信号，以使新的遥感方法能够在这些商业保护波段上用于精准农业，林业和水资源保护的各种实际解决方案中的科学用途。 该项目将在实际环境中展示新的低成本传感技术，并为农业经济做出贡献。 该技术旨在为全国和世界范围内的农业应用引入一系列精确灌溉，重点是经济贫困地区和发展中国家。 主要研究员（PI）的补充教育目标是在学生，公众和农民中产生对微波遥感的惊人世界及其对世界上最宝贵资源的非侵入性跟踪的认识和理解：植物和土壤中的水。该项目将支持PI努力扩大当今多元化学生的参与，包括代表性不足的少数群体，通过新的移动的应用程序，无人机，游戏和有趣的事实等活动进行STEM教育。该项目将构建基础微波遥感科学，一个破坏性的传感框架，以及集成的无处不在的平台，这些平台是非侵入性的，可广泛访问的，并且是自动化的，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）生成基于无人机的精准农业向微波波段转变所需的基础知识，（2）设计一个集成/连接的RF测试平台来评估新的范式，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土壤水分反演和现场验证来实现。具体而言，这项工作将通过回收小型无人机微波频谱中的低频发射，为根区土壤水分观测的准确水分监测提供科学依据。探索用于无人机遥感的低频微波频谱是前所未有的，因为现有的小型无人机仪器都无法在微波频谱中如此低的频率进行遥感。该项目将填补必要的科学基础，以评估该方法的可行性，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灌溉农业的水资源利用要求以及为RF辅助的基于UAS的精准农业的新范式创建算法非常重要。该奖项反映了NSF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而被认为值得支持。

项目成果

Fusion of Reflected GPS Signals With Multispectral Imagery to Estimate Soil Moisture at Subfield Scale From Small UAS Platforms

• DOI: 10.1109/jstars.2022.3197794
• 发表时间: 2022
• 期刊: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• 影响因子: 5.5
• 作者: V. Senyurek;M. Farhad;A. Gurbuz;M. Kurum;A. Adeli

A Realistic Framework of GNSS-T for Simulating Scattering and Propagation of GNSS Signals under a Forest Canopy

用于模拟森林冠层下 GNSS 信号散射和传播的现实 GNSS-T 框架

• 发表时间: 2023
• 期刊: PhotonIcs and Electromagnetics Research Symposium
• 作者: Suraj Yadav, Abesh Ghosh

A Ubiquitous GNSS-R Approach Using Spinning Smartphone Onboard a Small UAS

使用小型 UAS 上旋转智能手机的普遍 GNSS-R 方法

• DOI: 10.1109/igarss46834.2022.9883803
• 发表时间: 2022
• 期刊: 2022 IEEE International Geoscience and Remote Sensing Symposium
• 作者: Kurum, Mehmet;Farhad, Md Mehedi;Diao, Junming;Gurbuz, Ali C.
• 通讯作者: Gurbuz, Ali C.

Enabling subfield scale soil moisture mapping in near real-time by recycling L-band GNSS signals from drones

通过回收无人机的 L 波段 GNSS 信号，实现近乎实时的子田尺度土壤湿度测绘

• 发表时间: 2023
• 期刊: EGU General Assembly 2023
• 作者: Mehmet Kurum, Mehedi Farhad

Recent Results from P-Band Signals of Opportunity Receiver Deployed on a Multi-Copter Uas Platform

部署在多旋翼无人机平台上的机会接收器 P 波段信号的最新结果

• DOI: 10.1109/igarss46834.2022.9883795
• 发表时间: 2022
• 期刊: 2022 IEEE International Geoscience and Remote Sensing Symposium
• 作者: Kurum, Mehmet;Peranich, Preston;Shahid Rafi, Md Abdus;Farhad, Md Mehedi;Boyd, Dylan
• 通讯作者: Boyd, Dylan