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

在过去的二十年里，低成本、低功耗的硅射频集成电路(IC)的发展为毫米波(MmWave)的商业应用打开了大门，而毫米波的频率比今天用于WiFi和蜂窝的频率要高一个数量级。毫米波通信网络的大规模部署，如室外的NextG蜂窝基础设施和室内的NextG WiFi基础设施，意味着可以利用这些资源以其他方式无法实现的规模进行射频成像。该项目为这种联合通信和成像(JCAI)系统开发基本算法、体系结构和协议。这样一个系统中的每个传感器都提供4D测量(距离、多普勒、方位角和仰角)，这些测量的分辨率随着频率的提高而提高。该项目通过开发使用100 GHz以上频率的大规模射频成像，确立了美国在一项关键技术方面的领先地位。户外应用包括行人和车辆跟踪，以实现全球态势感知，支持车辆自主，并应对安全挑战，如及时检测非法无人机或未经授权的人员。在室内环境中，该技术能够对老年人护理和智能家居应用的人类行为进行细粒度的推理/预测。射频成像技术在可见光或红外线技术无效的低光或高烟雾/雾条件下特别有用。该项目开发并演示了毫米波频率下的联合计算机辅助教学的框架。该技术计划的一个核心方面是通过合成大孔径(推力1)大幅提高分辨率。这采用了单一传感器设计的新方法的组合，这些方法利用为通信而开发的大型天线阵列，以及多个传感器之间的网络协作。一个互补的方面(推力2)是战略性地利用无人驾驶车辆来成像难以到达的地区，利用固定的基础设施来减少机器人的有效载荷。在推力3中，私人投资机构以前开发的140 GHz通信硬件将被改装，以支持100 GHz的联网射频成像演示。推力4号开发了网络成像的控制面，包括基于成像需求和成像能力的资源管理框架，以及支持协同成像的协议。即将开发的概念和方法将对广泛的应用产生潜在影响，包括车辆自动驾驶和道路安全、制造自动化、室内和室外安全、老年人护理和医疗保健。PIS将与行业合作伙伴密切合作，以他们在过渡毫米波研究方面的良好记录为基础，并计划通过课程、顶峰项目和REU项目将这项研究纳入本科课程。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.