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.

在雷达，声纳，天文学，地震学和无线通信的领域中，检测目标及其出境方向起着关键作用。如果用接收器进行被动传感以分析截获的信号，则具有N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，并在所谓的自由度（DOF）度量的理论限制的指导下进行指导。 通过增加此类系统的能力，设计具有高DOF的传感系统可以从根本上提高感应，检测和估计的领域。进步有助于支持各种对国家安全和经济重要的应用和服务。该项目旨在开发一些基本技术来进行主动感测，以显着提高自由度度量的度量，并有助于许多应用依赖的感应，检测和估计的进步。调查人员将将项目材料纳入本科和研究生课程，并将促进代表性不足的群体的参与。这项工作属于两个主要推力：1）开发一个基本的主动合成共同阵列，可以利用同时使用原理使用原理。单独使用任何两种技术，都超过了MIMO雷达和共同阵列的传感限制； 2）设计一种新颖的两级高级稀疏阵列几何形状，该几何形状可以充分利用主动合成共阵列方法，并在两个级别中灵活地整合不同的阵列几何形状，以增加DOF多达四个订单，同时满足各种应用需求，以满足不同的应用需求。阵列结构。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估值得支持。