Collaborative Research: CNS Core: Large: 4D100: Foundations and Methods for City-scale 4D RF Imaging at 100+ GHz

合作研究：CNS 核心：大型：4D100：100 GHz 城市规模 4D 射频成像的基础和方法

• 批准号: 2215082
• 负责人: Ashutosh Sabharwal
• 金额: $ 24万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2215082&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Large

Advances in low-cost low-power silicon radio frequency (RF) integrated circuits (ICs) in the last two decades have opened up the commercial applications for millimeter wave (mmWave) frequencies which are an order of magnitude beyond those used in WiFi and cellular today. Large-scale deployment of mmWave communication networks, such as NextG cellular infrastructure outdoors and NextG WiFi infrastructure indoors, implies that these resources can be leveraged for RF imaging at scales that are not otherwise possible. The project develops foundational algorithms, architectures and protocols for such Joint Communication and Imaging (JCAI) systems. Each sensor in such a system provides 4D measurements (range, Doppler, azimuth angle and elevation angle) whose resolution improves by going to higher frequencies. The project establishes US leadership in a critical technology by developing large-scale RF imaging using frequencies beyond 100 GHz. Outdoor applications include pedestrian and vehicular tracking for global situational awareness supporting vehicular autonomy, and addressing security challenges such as timely detection of illegal drones or unauthorized personnel. In indoor settings, the technology enables fine-grained inference/prediction of human actions for eldercare and smart home applications. RF imaging technologies are especially useful in low-light or high-smoke/fog conditions when visible light or infrared technologies are not effective.The project develops and demonstrates a framework for JCAI at mmWave frequencies. A core aspect of the technical plan is to drastically improve resolution by synthesizing large apertures (Thrust 1). This employs a combination of novel approaches to single sensor design which utilize large antenna arrays developed for communication, and networked collaboration between multiple sensors. A complementary aspect (Thrust 2) is the strategic utilization of unmanned vehicles to image difficult-to-reach areas, utilizing the fixed infrastructure to reduce the robot payload. In Thrust 3, hardware at 140 GHz previously developed by the PIs for communication will be adapted to support demonstration of networked RF imaging at 100+ GHz. Thrust 4 develops a control plane for networked imaging, including a resource management framework based on imaging demand and imaging capacity, and protocols supporting collaborative imaging. The concepts and methods to be developed have potential impact in a vast array of applications, including vehicular autonomy and road safety, manufacturing automation, indoor and outdoor security, eldercare, and healthcare. The PIs will work closely with industry partners, building on their strong track record in transitioning mmWave research, and plan to incorporate this research into the undergraduate curriculum through courses, capstone projects, and REU projects.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.

在过去的二十年中，低成本的低成本硅射频（RF）集成电路（ICS）的进步已经打开了毫米波（MMWave）频率的商业应用，这是当今WiFi和细胞中使用的频率的数量级。 MMWave通信网络的大规模部署，例如在室外的NextG蜂窝基础架构和室内Nextg WiFi基础架构，这意味着可以利用这些资源来利用这些资源在不可能的尺度上进行RF成像。该项目开发了这种联合通信和成像（JCAI）系统的基础算法，架构和协议。这种系统中的每个传感器都提供4D测量（范围，多普勒，方位角和高程角），它们的分辨率通过较高的频率改善。 该项目通过使用超过100 GHz的频率开发大规模的RF成像来建立美国在关键技术中的领导。户外应用程序包括支持车辆自治的全球情境意识的行人和车辆跟踪，以及应对安全挑战，例如及时检测非法无人机或未经授权的人员。 在室内环境中，该技术可实现对老年护理和智能家庭应用的人类行为的细粒度推理/预测。当可见光或红外技术无效时，RF成像技术在低光或高烟/雾条件下特别有用。该项目在MMWave频率下开发并展示了JCAI的框架。 技术计划的一个核心方面是通过综合大量孔径（推力1）大大改善分辨率。这采用了新型方法的单个传感器设计的组合，利用用于通信的大型天线阵列以及多个传感器之间的联网协作。互补的方面（推力2）是利用固定的基础设施来减少机器人有效载荷的战略利用来对难以到达的区域进行图像形象。在推力3中，PIS先前开发的140 GHz的硬件将适应100+ GHz的网络RF成像的演示。 推力4开发用于网络成像的控制平面，包括基于成像需求和成像能力的资源管理框架以及支持协作成像的协议。要开发的概念和方法对包括车辆自治和道路安全，制造自动化，室内和室外安全，老年护理和医疗保健在内的各种应用都有潜在的影响。 PI将与行业合作伙伴紧密合作，基于他们在过渡MMWave研究方面的良好往绩，并计划通过课程，Capstone Projects和REU项目将这项研究纳入本科课程中。这项奖项反映了NSF的法定任务，并认为通过基金会的知识优点和广泛的crietia crietia criperia criperia criperia criperia criperia criperia criperia cripitia criperia criperia cripitia cripitia recteria rection tosection奖。