Robust Compressive Sensing: Circuits and Algorithms

鲁棒的压缩传感：电路和算法

• 批准号: 1201835
• 负责人: Dennis Goeckel
• 金额: $ 35.98万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2016-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1201835&HistoricalAwards=false
• 关键词: Robust; Compressive; Sensing; Circuits; Algorithms

Objective:The objective of this program is to co-design circuits and algorithms for compressive/low rate wideband receivers that are robust to the non-idealities that arise with the large interferers that will be encountered in sensing and communication applications. The program thus provides two transformative perspectives: (1) solving the interference problem in wideband applications using compressive sensing approaches, and (2) broadening the theoretical basis for compressive sensing to include systems with weak nonlinearity.Intellectual merit:The intellectual merit is centered around two thrusts that combine circuit and matched compressive sensing approaches: (1) By combining observations on circuits (devices are linear for small amplitudes) and compressive sensing (randomized subsampling is an effective acquisition approach for frequency-sparse signals), the project is designing nonlinearity-aware analog-to-information converters that select samples that preserve linearity in the measurement process; (2) By combining prior knowledge on the communication environment (characterizations of common interferers) with algorithmic tools for interference cancellation, the project is designing demodulator sequences and matched recovery algorithms that account for the nonlinearity of the analog-to-information converter and enable DSP-based interference cancellation.Broader Impacts:The broader impacts of this project include innovations that enable much more efficient use of the very valuable communication spectrum. Specifically, it affects the critical interference problem for wideband systems and the direction of the emerging field of compressive sensing. It impacts numerous applications, ranging from emerging cognitive radios to environmental sensing systems. Finally, the project includes an integrated program of active educational engagement at levels ranging from K-12 to graduate school.

目标：该计划的目标是为压缩/低速率宽带接收器共同设计电路和算法，这些接收器对于传感和通信应用中遇到的大干扰所产生的非理想情况具有鲁棒性。因此，该计划提供了两个变革性的视角：(1) 使用压缩传感方法解决宽带应用中的干扰问题，以及 (2) 拓宽压缩传感的理论基础，以包括具有弱非线性的系统。 智力优点：智力优点集中在将电路和匹配的压缩传感方法相结合的两个推力上：(1) 通过结合对电路的观察（器件对于小型器件是线性的） 幅度）和压缩传感（随机二次采样是频率稀疏信号的有效采集方法），该项目正在设计非线性感知模拟信息转换器，选择在测量过程中保持线性的样本； (2) 通过将通信环境的先验知识（常见干扰源的特征）与干扰消除的算法工具相结合，该项目正在设计解调器序列和匹配的恢复算法，以解决模拟信息转换器的非线性并实现基于 DSP 的干扰消除。 更广泛的影响：该项目的更广泛影响包括能够更有效地利用现有技术的创新。 宝贵的通信频谱。 具体来说，它影响宽带系统的关键干扰问题以及压缩感知新兴领域的方向。它影响着众多应用，从新兴的认知无线电到环境传感系统。最后，该项目包括一个积极参与教育的综合计划，涵盖从 K-12 到研究生院的各个级别。