High-speed Estimation and Control using Slow-rate Integrative Image Sensors for Adaptive Optics

使用低速集成图像传感器进行自适应光学的高速估计和控制

• 批准号: 1130231
• 负责人: Sandipan Mishra
• 金额: $ 35万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1130231&HistoricalAwards=false
• 关键词: speed; Estimation; Control; using; Slow

The research objective of this award is to realize high-speed adaptive optics (AO) systems that use slow-rate image sensors, such as charge-coupled device (CCD) or complementary metal?oxide?semiconductor (CMOS) arrays, for feedback. Such sensors are currently limited to only low bandwidth applications due to their relatively slow sampling rates. The proposed research will draw on the integrative nature of the image sensor to overcome this bandwidth limitation by combining estimation theory for multi-rate systems (from systems theory) and blur-to-motion algorithms (from image processing). Deliverables from this project include: (1) a system-theoretic analysis of the translation of the dynamics of an object into the spatial intensity distribution measured by an image sensor, (2) fast-rate, accurate, and robust output estimation and identification strategies using slow-rate image sensors; (3) tools for design and analysis of feedforward and feedback laws for systems with image sensors; and (4) demonstration of high-speed laser beam shaping and high-speed wavefront aberration correction for imaging systems. The successful completion of this project will enable the use of cost-effective slow-rate image sensors in high-speed applications, which is currently infeasible because of low bandwidth restrictions. Key insights obtained will thus impact not only high-performance AO systems but also other high-speed systems that rely on image sensor feedback, such as visual-servo robots, aero-optics turbulence measurement systems, and parallelized optical tweezers. Together with industrial partners, the results of this research will be disseminated to practitioners from diverse technologies, including laser processing and wafer inspection with high speed scanning. Graduate and undergraduate students engaged in this project will be trained for a unique interdisciplinary understanding of optics, systems theory, and image processing. The project will also introduce middle and high school students to the exciting area of adaptive optics through development of passive and active optical components embedded into controllable Lego blocks.

该奖项的研究目标是实现使用慢速图像传感器的高速自适应光学器件（AO）系统，例如电荷耦合器件（CCD）或互补金属？氧化物？半导体（CMOS）阵列，以获取反馈。 由于采样率相对较慢，因此此类传感器目前仅限于低带宽应用。拟议的研究将借鉴图像传感器的整合性，通过结合多率系统（来自系统理论）和模糊动作算法（来自图像处理）的估计理论来克服这一带宽限制。该项目的可交付成果包括：（1）对物体动力学转换为通过图像传感器测量的空间强度分布的转换的系统理论分析，（2）使用慢速速率图像传感器进行快速速率，准确且可靠的输出估计和识别策略； （3）用于设计和分析具有图像传感器系统的进料和反馈定律的工具； （4）演示成像系统的高速激光束塑形和高速波前像差校正。 该项目的成功完成将使在高速应用中使用具有成本效益的慢速图像传感器，这是由于带宽限制较低而目前不可行的。因此，获得的关键见解不仅会影响高性能AO系统，还会影响其他依赖图像传感器反馈的高速系统，例如Visual-Servo Robots，Aero-Optics湍流测量系统和并行的光镊。与工业合作伙伴一起，这项研究的结果将被分配给来自不同技术的从业者，包括激光处理和高速扫描的晶圆检查。从事该项目的研究生和本科生将接受对光学，系统理论和图像处理的独特跨学科理解的培训。该项目还将通过开发嵌入可控乐高积木中的被动和主动的光学组件来向中学生和高中生介绍自适应光学的令人兴奋的领域。