CAREER: Spatial Sensing for Design of Miniature Sensor Array Microsystems

职业：用于微型传感器阵列微系统设计的空间传感

• 批准号: 0846265
• 负责人: Milutin Stanacevic
• 金额: $ 40万
• 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: 2009
• 资助国家: 美国
• 起止时间: 2009-07-15 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0846265&HistoricalAwards=false
• 关键词: CAREER; Spatial; Sensing; Design; Miniature

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The focus of this research is the design of algorithms and real-time system implementations for the task of source localization and separation using miniature sensor arrays. The dimensions of the arrays are much smaller than the wavelength of the incident signals. The approach integrates wave-front sensing and independent component analysis in a framework that has the potential to extend the performance of current source separation algorithms and result in efficient implementation in mixed-signal very large-scale integration (VLSI) circuitry, yielding real-time performance in a small form factor. The extension of the algorithms under study to electromagnetic waves has the potential to significantly increase the efficiency of power transfer through inductive coupling for implantable biomedical devices. Extension to radio frequency (RF) waves presents an alternative solution for adaptive wideband beam-forming for compact smart antennas in portable devices.The miniaturization of sensors poses new challenges in sensor integration and presents new opportunities to advance the performance of current systems. The gradient flow method under investigation has the potential to advance the theory and practice of smart sensor array interfaces through the synergy of spatial and temporal sensing. The integration of this biologically-inspired concept has the potential to lead to important advances in solving the difficult "cocktail party" problem, separating and distinguishing signals in a noisy environment, observed in acoustics.The results of the proposed work have the potential to contribute to a number of applications including intelligent hearing aids, acoustic monitoring and surveillance in demanding environments, implantable neural interfaces, and portable communication devices. In addition to the project's scientific and engineering impact, the research has the potential to cultivate and introduce interdisciplinary approaches to engineering problems to undergraduate and graduate students through classes, projects, and workshops in analog integrated circuit design and sensory information processing.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。该研究的重点是使用微型传感器阵列进行源定位和分离任务的算法设计和实时系统实现。 阵列的尺寸远小于入射信号的波长。 该方法集成了波前传感和独立分量分析的框架，有可能扩展当前源分离算法的性能，并导致在混合信号超大规模集成（VLSI）电路中的有效实施，从而在一个小的形状因子的实时性能。 将研究中的算法扩展到电磁波，有可能通过可植入生物医学设备的电感耦合显著提高功率传输的效率。 射频（RF）波的扩展为便携式设备中紧凑型智能天线的自适应宽带波束形成提供了一种替代解决方案。传感器的小型化对传感器集成提出了新的挑战，并为提高当前系统的性能提供了新的机会。 研究中的梯度流方法具有通过空间和时间感测的协同来推进智能传感器阵列接口的理论和实践的潜力。 这一生物启发的概念的整合有可能导致解决困难的“鸡尾酒会”问题的重要进展，分离和区分噪声环境中的信号，在声学中观察到。拟议工作的结果有可能有助于许多应用，包括智能助听器，在苛刻环境中的声学监测和监视，植入式神经接口，和便携式通信设备。 除了该项目的科学和工程影响，该研究有可能通过模拟集成电路设计和传感信息处理的课程，项目和研讨会，为本科生和研究生培养和引入跨学科的工程问题方法。