EAGER: Heterogeneous Sensor Network Design and Information Integration
EAGER: Heterogeneous Sensor Network Design and Information Integration
批准号:
0956438
负责人:
Qilian Liang
金额:
$10.0万
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
项目状态:
已结题
起止时间:
2009-09-15 至 2011-08-31
中文摘要
智力优势:该项目的目标是为异构传感器网络(HSN)开发信息理论和基于信号处理的算法,共同解决约束环境中固定或非固定异构传感器组合存在的传感器适应和数据融合问题。本文将探讨两个研究重点:1)HSN设计的信息理论;2) HSN信息集成的信号处理。目前对HSN理论和算法的研究非常有限。有许多根本问题从未得到解决,但它们对高铁至关重要。为了解决这些问题,将研究新的方法和方法,这些方法和方法将结合信息理论、网络科学、协作信号处理、估计理论、统计方法和优化等技术,因此有可能激发可应用于许多领域的变革方法。所提出的理论将导致实用的方法、算法和设计工具,其性能对不确定性具有鲁棒性,并能适应动态操作条件的变化。更广泛的影响:本项目将对高铁的应用作出重大贡献,并将产生广泛而深刻的社会影响。由于国土安全和国防中的大量实时信息来自许多广泛分布的来源,因此需要HSN收集和处理与威胁相关的信息,以确保这些信息不会被忽视。还提出了一个精心制定的、以研究为中心的教育计划。该项目将从不同的社团招募代表性不足的女学生。
英文摘要
Intellectual Merits: The objective of this project is to develop information theory and signal processing-based algorithms for Heterogeneous Sensor Networks (HSN) that jointly addresses sensor adaptation and data fusion in the presence of a combination of stationary or non-stationary heterogeneous sensors in constrained environments. Two research thrusts will be investigated: 1) information theory for HSN design; 2) signal processing for HSN information integration. Current research on the theory and algorithms of HSN is very limited. There exist a number of fundamental problems that have never been addressed, yet they are critical to the HSN. To tackle these problems, novel approaches and methodologies that will incorporate techniques such as information theory, network science, collaborative signal processing, estimation theory, statistical approach, and optimization will be studied and therefore has the potential to inspire transformative methodologies that could be applied to many domains. The proposed theories will lead to practical methodologies, algorithms and design tools with performance robust to uncertainty and adaptive to variations in dynamic operating conditions.Broader Impacts: This project will make a significant contribution to the applications of HSN and will have a broad and deep social impact. Because of the vast amounts of real-time information coming from many widely distributed sources in homeland security and defense, HSN is needed to collect and process threat-related information to insure that it is not overlooked. A carefully developed, research-centric education plan is also proposed. Under-represented and female students will be recruited from different societies for this project.
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