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

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:
$50.0万
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
项目状态:
已结题
起止时间:
2022-05-01 至 2023-12-31

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中文摘要
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英文摘要
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.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
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]
通讯作者: 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
DOI: --
发表时间: 2023
期刊: PhotonIcs and Electromagnetics Research Symposium
影响因子: --
作者: [Suraj Yadav, Abesh Ghosh]
通讯作者: 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
影响因子: --
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
DOI: --
发表时间: 2023
期刊: EGU General Assembly 2023
影响因子: --
作者: [Mehmet Kurum, Mehedi Farhad]
通讯作者: Mehmet Kurum, Mehedi Farhad
Collaborative Research: SWIFT-SAT: INtegrated Testbed Ensuring Resilient Active/Passive CoexisTence (INTERACT): End-to-End Learning-Based Interference Mitigation for Radiometers
  • 批准号:
    2332662
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2024
  • 负责人:
    Mehmet Kurum
  • 依托单位:
CAREER: Recycling the Radio Spectrum for Science: A New Paradigm for UAS-based Precision Agriculture
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