Signal Processing for Passive RF Sensing

该项目考虑采用无线通信信号作为机会照明器（IO）来检测，定位和跟踪感兴趣的对象的无源射频（RF）传感。这样的能力对于广泛的应用是有用的，室内定位、健康监测、车辆跟踪等等。最初被认为是主动感测的补充技术（例如，雷达），被动射频传感已成为一个有前途的替代方案，远远超出了标准雷达操作的范围。无源射频传感与有源传感相比具有许多优势：没有专用发射机，无射频污染;隐蔽操作;建造，部署和操作的数量级更便宜;能够同时访问多个IO以获得监视区域的多个视图和空间多样性。最近对被动RF感测的兴趣进一步受到频谱稀缺和无线部门释放政府持有的频谱（包括分配给主动感测的频谱）以促进经济增长的压力的推动。鉴于无线基础设施的普遍存在，预计无源RF传感将融入人们的日常生活。例如，无线服务提供商可以提供具有内置无源RF传感功能的无线设备，并使其广泛适用于任何用户。因此，相关的经济和社会影响的拟议研究是substantial.Despite的优势，有一些基本的技术问题，需要调查的被动射频传感。具体而言，与具有基于匹配滤波器（MF）的最佳信号处理的完善理论的有源传感不同，现有的无源传感技术主要通过模仿MF来引入，而没有充分考虑两个系统之间的差异。MF需要传输波形的知识，由于IO的非合作性质，这在无源系统中是不可用的。标准策略是用参考信号来代替它，参考信号是通过朝向IO的天线获得的IO波形的噪声副本，并且将参考信号与接收信号进行互相关（CC）。CC检测器不是最佳方法。事实上，它对参考中包含的噪声非常敏感，并且由于直接路径干扰而进一步恶化，即，从IO到被动接收器的直接传输。为了解决这些问题，该项目的目的是开发新的信号处理技术，无源射频传感考虑到损伤，如噪声参考，DPI和多径杂波，这是固有的无源系统。此外，该项目还将开发被动射频传感技术，包括放置在移动平台上的传感器（例如，无人驾驶飞行器）来获得场景的特写，这对于救灾、农村搜索和许多其它应用是有意义的。一个主要的技术挑战是科普平台运动引起的过度杂波多普勒扩展。最后，该项目还具有重要的教育组成部分，旨在为本科生和研究生提供综合研究经验和培训。

This project considers passive radio frequency (RF) sensing that employs wireless communication signals as illuminators of opportunities (IOs) to detect, locate, and track objects of interest. Such capabilities are useful for a wide range of applications, e.g., indoor localization, health monitoring, vehicle tracking, and many more. Originally considered as a supplementary technology to active sensing (e.g., radar), passive RF sensing has emerged as a promising alternative that far exceeds the scope of standard radar operations. Passive RF sensing has many advantages over its active counterpart: no dedicated transmitter and RF pollution free; covert operation; order of magnitude cheaper to build, deploy and operate; and the ability to simultaneously access several IOs to obtain multiple views and spatial diversity of the surveillance area. Recent interest in passive RF sensing is further driven by spectrum scarcity and a growing pressure from the wireless sector to release government-held spectrum, including spectrum allocated to active sensing, in order to boost the economy. Given the ubiquity of wireless infrastructure, it is expected that passive RF sensing will be integrated in people's daily life. For example, wireless service providers can offer wireless devices with built-in passive RF sensing functions and make them broadly available to any user. Thus, the associated economical and societal impact of the proposed research is substantial.Despite the advantages, there are fundamental technical issues that need to be investigated for passive RF sensing. Specifically, unlike active sensing which has a well-established theory for optimum signal processing based on the matched filter (MF), existing passive sensing techniques were introduced largely by imitating the MF, without adequately considering the differences between the two systems. The MF requires knowledge of the transmitted waveform that is unavailable in a passive system due to the non-cooperative nature of the IO. The standard strategy is to replace it with a reference signal, which is a noisy copy of the IO waveform obtained via an antenna steered toward the IO, and cross-correlates (CC) the reference signal with the received signal. The CC detector is not an optimal method. In fact, it is very sensitive to the noise contained in the reference and further deteriorated by the direct-path interference, i.e., the direct transmission from the IO to the passive receiver. To address these issues, this project aims to develop novel signal processing techniques for passive RF sensing by taking into account impairments such as noisy reference, DPI, and multi-path clutter, which are inherent in passive systems. In addition, the project will develop techniques for passive RF sensing involving sensors placed on moving platforms (e.g., unmanned aerial vehicles) to obtain close-up looks of the scene, which is of interest for disaster relief, rural search, and many other applications. A major technical challenge there is to cope with excessive clutter Doppler spread induced by platform motion. Finally, this project also has a significant educational component aimed to provide integrated research experience and training for undergraduate and graduate students.