EAGER: Heterogeneous Sensor Network Design and Information Integration

EAGER：异构传感器网络设计和信息集成

基本信息

批准号：
0956438
负责人：
Qilian Liang
金额：
$ 10万
依托单位：
University of Texas at Arlington
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：
2009-09-15 至 2011-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0956438&HistoricalAwards=false
关键词：
EAGER Heterogeneous Sensor Network Design

项目摘要

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.

智力优点：该项目的目的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，该算法在约束环境中共同解决传感器适应和数据融合。将研究两个研究推力：1）HSN设计的信息理论； 2）HSN信息集成的信号处理。当前对HSN理论和算法的研究非常有限。存在许多从未解决的基本问题，但它们对HSN至关重要。为了解决这些问题，将研究诸如信息理论，网络科学，协作信号处理，估计理论，统计方法和优化等技术的新颖方法和方法论，因此有可能激发可以应用于许多领域的变革性方法。拟议的理论将导致实用方法，算法和设计工具具有强大的性能，对不确定性和适应动态操作条件的变化。BRODER的影响：该项目将对HSN的应用做出重大贡献，并将产生广泛而深厚的社会影响。由于来自国土安全性和国防部广泛分布的来源的大量实时信息，需要HSN来收集和处理与威胁相关的信息，以确保不忽略它。还提出了一项精心开发的以研究为中心的教育计划。该项目将从不同的社会中招募代表性不足和女学生。