CIF: Small: Improving Sensing and Estimation with Co-array Techniques

CIF：小型：利用联合阵列技术改进传感和估计

• 批准号: 2007313
• 负责人: Xin Wang
• 金额: $ 16万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2007313&HistoricalAwards=false
• 关键词: CIF; Small; Improving; Sensing; Estimation

Detecting targets and their direction-of-arrival plays a key role in the areas of radar, sonar, astronomy, seismology and wireless communications. In the case of passive sensing with a receiver to just analyze signals intercepted, a uniform linear sensing array with N physical sensors can identify at most N - 1 targets, guided by the theoretical limit of the so-called degree of freedom (DoF) metric. Designing a sensing system with high DoF can fundamentally advance the field of sensing, detection and estimation, by increasing the capacity of such systems. The advancement is instrumental to support various applications and services that are important for national security and the economy. This project seeks to develop some fundamental techniques for active sensing to significantly increase the degree-of-freedom metric, and contribute to the advancement of sensing, detection and estimation that many applications depend upon. The investigator will incorporate the project materials into both undergraduate and graduate courses, and will facilitate participation from under-represented groups.The work falls into two major thrusts: 1) Developing a fundamental Active Synthetic Co-array that can exploit the concurrent use of principles of MIMO radar and co-arrays to surpass the sensing limit from the use of either technique alone; 2) Designing a novel two-level advanced sparse array geometry that can take full advantage of the active synthetic co-array method and flexibly integrate different array geometries in the two levels to increase the DoF up to four orders while meeting various application needs with different array structures.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.

检测目标及其到达方向在雷达、声纳、天文学、地震学和无线通信领域发挥着关键作用。在使用接收器仅分析截获信号的被动传感的情况下，具有 N 个物理传感器的均匀线性传感阵列最多可以识别 N - 1 个目标，并以所谓的自由度 (DoF) 指标的理论极限为指导。 设计具有高自由度的传感系统可以通过增加此类系统的容量，从根本上推进传感、检测和估计领域的发展。这一进步有助于支持对国家安全和经济至关重要的各种应用程序和服务。该项目旨在开发一些主动传感的基本技术，以显着增加自由度度量，并为许多应用所依赖的传感、检测和估计的进步做出贡献。研究人员将把项目材料纳入本科生和研究生课程中，并将促进代表性不足群体的参与。这项工作分为两个主要方向：1）开发一种基本的有源合成协同阵列，可以利用同时使用 MIMO 雷达和协同阵列原理来超越单独使用任一技术的传感极限； 2）设计一种新颖的两级先进稀疏阵列几何结构，可以充分利用有源合成共阵列方法，并在两级中灵活地集成不同的阵列几何结构，将自由度提高到四个数量级，同时满足不同阵列结构的各种应用需求。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，认为值得支持。