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.

由于物联网 (IoT)、无人机系统 (UAS) 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快速增长，不幸的是，有源无线系统的增长往往会增加无线电频率。就目前而言，科学观测中的射频干扰（RFI）很少，专用于科学的射频频谱很少，并且少量可用频谱可能会受到邻近射频干扰的影响，或者在干扰发生后重新分配用于商业用途。对带宽的需求不断增长该项目的重点是改变遥感方法的范式，开发频谱效率更高、更有效的下一代技术和想法，并应对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，以在这些商业保护频段上实现新的遥感方法，以便在精准农业、林业、水资源保护的无数实际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传感技术，并有助于促进可持续发展。发达的技术旨在迎来农业经济。首席研究员 (PI) 的补充教育目标是提高学生、公众和农民对农业精准灌溉的认识和理解。微波遥感的奇妙世界及其对世界上最宝贵的资源（植物和土壤中的水）进行非侵入式跟踪的实用性该项目将支持 PI 的努力，以扩大当今多元化学生（包括代表性不足的少数群体）的参与。通过活动进行 STEM 教育例如新的移动应用程序、无人机、游戏和有趣的事实，该项目将构建基础的微波遥感科学、颠覆性的传感框架以及非侵入性、可广泛访问和自动化的集成无处不在的平台，以提高水的利用率。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/连接射频测试台，以及(3) 集成智能手机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以及现场验证来实现。具体来说，这项工作将为准确的水提供科学基础。通过回收小型无人机微波频谱中的低频发射来监测根区土壤湿度观测是前所未有的，因为现有的小型无人机仪器无法在如此低的频率下进行遥感。在微波频谱中。该项目将填补必要的科学基础来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雨养农业的用水要求以及创建新的算法非常重要。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，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

将反射 GPS 信号与多光谱图像融合，估算小型 UAS 平台子场范围内的土壤湿度

• DOI: 10.1109/jstars.2022.3197794
• 发表时间: 2024-09-13
• 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
• 通讯作者: A. Adeli

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: 2022-07
• 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.

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: 2023-01
• 期刊: PhotonIcs and Electromagnetics Research Symposium
• 作者: Suraj Yadav; Abesh Ghosh
• 通讯作者: Abesh Ghosh

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: 2023-04
• 期刊: EGU General Assembly 2023
• 作者: Mehmet Kurum; Mehedi Farhad
• 通讯作者: 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: 2022-07
• 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