I/UCRC: FRP:Sensor Fusion Research for Net-Centric Applications

提出的研究目标是传感器网络的基础工作。具体来说，这项工作解决了一个中心问题，即分布式推理系统需要对各种感知和通道损伤具有健壮性。这项工作旨在为传感器网络和以网络为中心的应用设计一套健壮的、分布式的检测和估计算法。提出了一种在最小假设感知噪声的情况下，对多种通信通道和拓扑结构进行稳健分布式推理的综合方法。拟议工作的结果有可能极大地影响许多以网络为中心的应用，包括环境、军事和医疗保健，这些应用需要聚合仅通过无线手段连接的传感器的数据。这项工作得到了行业咨询委员会以及该中心个别行业成员的支持，并有可能扩大S中心的投资组合，同时可能吸引新的成员。PI与HBCU学院合作了TUES第三阶段软件项目，将利用该项目招募少数族裔学生参加与该I/UCRC FRP相关的博士课程培训。

The proposed research targets fundamental work in sensor networks. Specifically the work addresses the central problem that distributed inference systems need to be robust to a wide variety of sensing, and channel impairments. The effort seeks to design a suite of robust, distributed detection and estimation algorithms for sensor networks and Net-Centric applications. A comprehensive approach to robust distributed inference for a wide range of communication channels and topologies, with minimal assumptions about the sensing noise, is proposed. The outcomes of the proposed work have the potential to greatly impact many Net-Centric applications including environmental, military and health care that require aggregation of data from sensors which are linked only through wireless means. The work is supported by the Industry Advisory Board as well as individual industry members of the center and has the potential to extend the center?s portfolio while potentially attracting new members. The PI has collaborative TUES Phase 3 software project with HBCU colleges that will be tapped on for recruitment of minority students for training in the Ph.D. program associated with this I/UCRC FRP.