A Scalable Configurable Acoustic Processor for Emerging Audio Applications

适用于新兴音频应用的可扩展可配置声学处理器

• 批准号: 2153821
• 负责人: Michael Flynn
• 金额: $ 36.97万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2153821&HistoricalAwards=false
• 关键词: Scalable; Configurable; Acoustic; Processor; Emerging

Very large acoustic transducer arrays will transform how we sense, generate, and manipulate sound. However, existing acoustic processing systems are not able to support large arrays. This project tackles the challenges of scale, time accuracy, latency and synchronization in large acoustic arrays. The research of this project will free acoustic arrays from the electronic performance bottlenecks that impede large-scale operation. The new audio technologies involving large-scale electro-acoustic systems promise transformative acoustic applications and will have the potential to transform biology and medicine through contactless manipulation and surgery. For example, high-resolution acoustic holography promises contactless manipulation of biological specimens, non-invasive surgery, and new modes for augmented reality. By providing detailed soundscapes, large sensitive arrays allow new levels of environmental and industrial monitoring. For example, high precision acoustic imaging can locate wildlife, pinpoint machine faults, and identify noise from wind turbines. In addition, active metamaterials will enable the construction and control of soundscapes. These materials can manage the sound environment in weight-sensitive aerospace applications and provide health benefits by targeting the sound debris that litters urban environments. For example, large active metamaterial surfaces can quieten aircraft cabins or even enable acoustic invisibility. The project will introduce sound processing in the undergraduate circuits curriculum and use sounds, instead of optics and electromagnetics, to provide an intuitive understanding of challenging applied physics concepts such as holography and metamaterials. This research will provide rewarding and meaningful research opportunities for undergraduate and high-school students. This project will tackle scale, time, and signal-to-noise ratio (SNR) challenges of emerging acoustic applications and transform audio processing with new mixed-signal circuit techniques that deliver unprecedented spatial resolution, temporal resolution, and dynamic range for emerging acoustic applications. The scale, which corresponds to the number of transducers, ultimately determines the resolution and the SNR. Furthermore, practical applications such as acoustic metamaterials work best on a large scale. Another challenge for large arrays is temporal accuracy through phase control and precise time synchronization. The research will investigate new techniques to address the critical scale, time resolution, and latency problems that impede large-scale acoustic holography, acoustic imaging, and active acoustic metamaterials. In addition, the research will address issues of synchronization and distributed processing for large-scale arrayed systems. The new techniques will enable large-scale high-fidelity systems with unprecedented time accuracy, time control, and low latency. The project will use testbed systems to showcase the potential of the new techniques. Finally, the research will explore the potential tradeoffs of configurable mixed-signal processing of bitstream.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.

非常大的声音传感器阵列将改变我们的感觉，产生和操纵声音。但是，现有的声学处理系统无法支持大型阵列。该项目应对大声阵列中规模，时间准确性，延迟和同步的挑战。该项目的研究将使声学阵列从阻碍大型操作的电子性能瓶颈中释放出声学阵列。涉及大规模电声系统的新音频技术有望变革性的声学应用，并有可能通过非接触式操纵和手术来转化生物学和医学。例如，高分辨率的声学全息图有望无接触式操纵生物标本，非侵入性手术以及增强现实的新模式。通过提供详细的音景，较大的敏感阵列可以提供新的环境和工业监测水平。例如，高精度的声学成像可以定位野生动植物，查明机器故障并确定风力涡轮机的噪声。此外，主动的超材料将实现音景的构建和控制。这些材料可以在体重敏感的航空航天应用中管理声音环境，并通过针对垃圾城市环境的声音碎片来提供健康益处。例如，大型主动的超材料表面可以使飞机舱安静，甚至启用声音隐形。该项目将在本科电路课程中引入声音处理，并使用声音，而不是光学和电磁学，以提供对挑战性应用物理概念（例如全息图和超材料）的直观理解。这项研究将为本科和高中生提供有意义且有意义的研究机会。该项目将解决新兴的声学应用的量表，时间和信噪比（SNR）挑战，并使用新的混合信号电路技术来转化音频处理，这些技术为新兴的声学应用提供了前所未有的空间分辨率，时间分辨率和动态范围。与传感器数量相对应的比例最终决定了分辨率和SNR。此外，诸如声学超材料之类的实际应用在大规模上最有效。大型阵列的另一个挑战是通过相位控制和精确的时间同步进行时间精度。这项研究将研究新技术，以解决阻碍大规模的声学全息，声学成像和主动声学超材料的临界量表，时间分辨率和延迟问题。此外，该研究将解决大型阵列系统的同步和分布式处理问题。新技术将使具有前所未有的时间准确性，时间控制和低潜伏期的大规模高保真系统。该项目将使用测试床系统来展示新技术的潜力。最后，该研究将探讨BITSTREAM的可配置混合信号处理的潜在权衡。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。