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

拟议的研究目标在传感器网络的基础工作。 具体来说，这项工作解决了分布式推理系统需要对各种各样的传感和信道损伤具有鲁棒性的核心问题。 这项工作旨在为传感器网络和网络中心应用设计一套鲁棒的分布式检测和估计算法。一个全面的方法来强大的分布式推理的广泛的通信信道和拓扑结构，最小的假设的传感噪声，提出了。拟议工作的结果有可能极大地影响许多网络中心的应用，包括环境，军事和医疗保健，这些应用需要从传感器中聚合数据，这些传感器仅通过无线方式连接。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，并有可能扩大该中心？的投资组合，同时有可能吸引新成员。PI与HBCU学院合作了TUES第三阶段软件项目，该项目将用于招募少数民族学生进行博士培训。与此I/UCRC FRP相关的程序。

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.