SpecEES: Cooperative Green RF Sensing over Shared Spectrum

SpecEES：共享频谱上的协作绿色射频传感

• 批准号: 1923739
• 负责人: Hongbin Li
• 金额: $ 75万
• 依托单位: Stevens Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1923739&HistoricalAwards=false
• 关键词: SpecEES; Cooperative; Green; RF; Sensing

Radar occupies a significant fraction of the spectrum below 6 GHz. This is a highly congested frequency band also heavily used by wireless communications. In recent years, there has been a growing demand from the wireless sector to free up more of the government-held spectrum, including those allocated to radar, in order to expand mobile broadband capabilities, promote wireless innovation, and boost the economy. Nonetheless, radar stakeholders are often unwilling to share their spectrum due to lack of incentives, as well as concerns over interference from the wireless communication devices that can disrupt the radar operation. This project considers such a spectrum-sharing scenario between radar and wireless communications and proposes a set of research efforts that are aimed to motivate radar stakeholders to open their spectrum for sharing. Specifically, it will develop new spectrum sharing protocols and cooperative radio frequency (RF) sensing techniques that protect, secure, and incentivize the radar users with reward of energy efficiency and enhanced sensing capabilities bestowed by sharing. The proposed research is expected to provide win-win solutions that will not only enable the radar to better detect, image, identify, and track targets with higher energy efficiency, but also allow wireless devices to enjoy significantly improved spectrum access opportunities. On the educational front, this project will offer opportunities for curricula development, training of undergraduate and graduate students, summer research programs targeting local high school students, and recruitment of students from underrepresented groups to this project.This project targets a spectrum sharing scenario, where radar owns and is willing to share its spectrum with wireless communication users under the condition that the radar operation is not to be compromised. The proposed efforts are integrated through the following four research thrusts: (1) a radar-centric cooperative design framework for spectrum sharing that protects the radar while improving the wireless communications; (2) a cooperative illumination approach that allows the radar to exploit wireless communication sources as passive illuminators; (3) a cooperative RF sensing paradigm whereby the radar and multiple spectrum-sharing communication devices cooperatively perform a distributed RF sensing task; and (4) security and privacy with radar and communication cross design that capitalizes on a new hybrid authentication scheme using integrated cryptographic credentials and non-cryptographic device fingerprints. The proposed RF sensing framework allows the radar to constructively employ co-channel communication sources as passive illuminators, which provide free illumination power and, more importantly, additional multi-static sensing geometries that enable the radar to achieve enhanced sensing capability and energy efficiency, i.e., the green RF sensing. To address the security and privacy issues inherent in the proposed framework, this project will develop a new hybrid authentication scheme that leverages unique device fingerprints and data analytics tools including deep learning to secure the proposed spectrum sharing and cooperative sensing solutions.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.

雷达占6 GHz以下光谱的很大一部分。这是一个高度拥挤的频带，也被无线通信大量使用。近年来，无线部门的需求越来越多，以释放更多政府拥有的范围，包括分配给雷达的范围，以扩大移动宽带能力，促进无线创新并促进经济。尽管如此，由于缺乏激励措施，雷达利益相关者通常不愿意分享他们的频谱，以及对可能破坏雷达操作的无线通信设备干扰的担忧。该项目考虑了雷达和无线通信之间的频谱共享方案，并提出了一系列研究工作，旨在激励雷达利益相关者开放他们的分享频谱。具体而言，它将开发新的频谱共享协议和合作射频（RF）传感技术，以保护，保护和激励雷达用户，并奖励能源效率，并通过共享获得增强的感应能力。拟议的研究预计将提供双赢解决方案，不仅可以使雷达更好地检测，图像，识别和跟踪具有较高能效的目标，而且还可以使无线设备享受明显改善的频谱访问机会。 On the educational front, this project will offer opportunities for curricula development, training of undergraduate and graduate students, summer research programs targeting local high school students, and recruitment of students from underrepresented groups to this project.This project targets a spectrum sharing scenario, where radar owns and is willing to share its spectrum with wireless communication users under the condition that the radar operation is not to be compromised.提出的努力通过以下四个研究作用进行了整合：（1）以雷达为中心的合作设计框架用于频谱共享，可以保护雷达，同时改善无线通信； （2）一种合作照明方法，允许雷达将无线通信来源作为被动照明器； （3）合作的RF传感范式，雷达和多个频谱共享通信设备合作执行分布式的RF感应任务； （4）使用雷达和通信交叉设计的安全性和隐私设计，该设计使用集成的加密凭据和非加密设备指纹在新的混合身份验证方案上大写。提出的RF传感框架使雷达可以用作被动照明器的共同通信源，从而提供自由照明功率，更重要的是，更重要的是，其他多静电传感几何形状，使雷达能够实现增强的感应能力和能量效率，即绿色RF感应。为了解决拟议框架中固有的安全性和隐私问题，该项目将开发一种新的混合身份验证方案，该方案利用独特的设备指纹和数据分析工具，包括深度学习，以确保拟议的频谱共享和合作感官解决方案。该奖项颁发了NSF的法定任务，并反映了通过评估范围的支持者，该奖项已被评估构成构成商业的支持和基础。

项目成果

An Overview of Parametric Modeling and Methods for Radar Target Detection With Limited Data

有限数据下雷达目标检测参数化建模和方法概述

• DOI: 10.1109/access.2021.3074063
• 发表时间: 2021
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Wang, Fangzhou;Wang, Pu;Zhang, Xin;Li, Hongbin;Himed, Braham
• 通讯作者: Himed, Braham

Target Detection With Imperfect Waveform Separation in Distributed MIMO Radar

• DOI: 10.1109/tsp.2020.2964227
• 发表时间: 2020-01-01
• 期刊: IEEE TRANSACTIONS ON SIGNAL PROCESSING
• 影响因子: 5.4
• 作者: Wang, Pu;Li, Hongbin
• 通讯作者: Li, Hongbin

Joint Waveform and Receiver Design for Co-Channel Hybrid Active-Passive Sensing With Timing Uncertainty

• DOI: 10.1109/tsp.2020.2964194
• 发表时间: 2019-08
• 期刊: IEEE Transactions on Signal Processing
• 影响因子: 5.4
• 作者: Fangzhou Wang;Hongbin Li

Delay Compensation for Distributed MIMO Radar With Non-Orthogonal Waveforms

非正交波形分布式 MIMO 雷达的延迟补偿

• DOI: 10.1109/lsp.2021.3123582
• 发表时间: 2022
• 期刊: IEEE Signal Processing Letters
• 影响因子: 3.9
• 作者: Zeng, Cengcang;Wang, Fangzhou;Li, Hongbin;Govoni, Mark A.
• 通讯作者: Govoni, Mark A.

An Efficient Method for Cooperative Multi-Target Localization in Automotive Radar

汽车雷达多目标协同定位的有效方法

• DOI: 10.1109/lsp.2021.3121626
• 发表时间: 2022
• 期刊: IEEE Signal Processing Letters
• 影响因子: 3.9
• 作者: Zhang, Xudong;Wang, Fangzhou;Li, Hongbin
• 通讯作者: Li, Hongbin