Collaborative Research: SWIFT: SCISRS: Signal Cancellation using Intelligent Surfaces for Radio Astronomy Services

该项目研究使用安装在射电望远镜附近的可重新配置的智能表面(RIS)来帮助减少来自电磁频谱的其他用户的射频干扰(RFI)。RIS将传入的RFI信号反射到望远镜，使得当两个信号在望远镜接收器中合并时，反射的RFI抵消了直接的RFI。更好地在商业无线频段和其他活跃使用的频段进行观测，而不仅仅是在为科学保留的频段上进行观测，将提高天文测量的保真度。此外，以前建造射电望远镜的偏远地区正在经历人口密度的持续增长、低地球轨道卫星数量的增加，以及随着时间的推移增加RFI的其他影响。提高从天文观测中去除RFI的能力有助于保护对这些昂贵仪器的投资价值，并有助于确保它们继续具有科学能力。在这个项目中开发的平台和工具将被纳入UAlbany的研究生和本科课程以及OVRO的暑期学校。从试验台捕获的无线信号和其他数据集将提供给更大的社区，以促进该领域的实际研究。该项目的主要技术目标是准确估计望远镜的RFI入射，并配置RIS，以便到达望远镜接收器的反射信号准确地抵消入射RFI。消除需要控制反射信号的幅度和相位，这是通过调节智能表面的反射元件来实现的。研究中解决的一个关键挑战是取消飞机和卫星等移动RFI源。移动信号源强调RIS控制器跟上RFI方向变化的能力，以及控制器保持表面足够精确地调整以消除RFI的能力。该项目结合了三个领域的创新来克服这一挑战。在系统级，RIS控制器使用来自望远镜的反馈，望远镜不断报告它看到的残余RFI，以补偿估计误差。在算法层面，将一种新的、低复杂度的多级波达方向估计方法与自适应波束形成算法相结合，对反射的射频干扰进行整形和引导。在硬件层面，由现场可编程门阵列构建的16通道高速处理平台与定制的RIS相耦合，以实现实时RFI估计和自适应波束形成。该项目将在纽约州立大学奥尔巴尼分校(UAlbany)建造一个基于麻省理工学院干草堆天文台小型射电望远镜(SRT)设计的实验射电望远镜。取消方法将在UAlbany SRT和欧文斯山谷射电天文台(OVRO)的大型DSA-110望远镜阵列的一个天线上进行测试。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。

This project investigates use of a reconfigurable intelligent surface (RIS) installed near a radio telescope to help mitigate radio frequency interference (RFI) from other users of the electromagnetic spectrum. The RIS reflects incoming RFI signals towards the telescope in such a way that the reflected RFI cancels out the direct RFI when the two signals combine in the telescope receiver. Better capability to observe in commercial wireless bands and in other bands with active usage, not just in bands reserved for science, will enhance the fidelity of astronomical measurements. Also, the formerly remote locations where radio telescopes were built are experiencing ongoing increases in population density, increased numbers of low earth orbiting satellites, and other effects that increase RFI over time. Improving the ability to remove RFI from astronomical observations helps preserve the value of the investment in these expensive instruments and helps ensure their continued scientific capability. The platform and tools developed in this project will be incorporated into graduate and undergraduate courses at UAlbany as well as a summer school at OVRO. Wireless signals and other datasets captured from the testbed will be made available to the larger community to foster practical research in this field.The primary technical objectives of this project are to accurately estimate the RFI incident at the telescope and to configure the RIS so the reflected signal arriving at the telescope receiver precisely cancels the incident RFI. Cancellation requires control over both amplitude and phase of the reflected signal, which is achieved by tuning the reflecting elements of the intelligent surface. A key challenge tackled in the research is to cancel mobile RFI sources such as airplanes and satellites. Mobile sources stress the ability of the RIS controller to keep up with changes in the direction of RFI and the controller’s ability to keep the surface tuned precisely enough to cancel the RFI. The project combines three areas of innovation to overcome this challenge. At the system level, the RIS controller uses feedback from the telescope, which continually reports the residual RFI it sees, to compensate for estimation errors. At the algorithm level, a novel, low-complexity multi-stage direction of arrival estimation method is combined with an adaptive beamforming algorithm that shapes and steers the reflected RFI. At the hardware level, a 16-channel high-speed processing platform built from Field Programmable Gate Arrays is coupled with a custom fabricated RIS to enable real time RFI estimation and adaptive beamforming. The project will construct an experimental radio telescope at University at Albany, SUNY (UAlbany) based on the Small Radio Telescope (SRT) design from MIT Haystack Observatory. The cancellation approach will be tested on the UAlbany SRT and on one antenna of the large DSA-110 telescope array at the Owens Valley Radio Observatory (OVRO).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.