PECASE: Compressive Cooperative Sensing and Navigation in Mobile Networks

本学院早期职业发展（CAREER）项目的研究目标是从压缩采样的角度开发移动的合作网络中的传感和导航的基础。移动的协作网络面临着其环境中丰富的信息。由于没有足够的时间直接测量整个地形，找到所需的基本最小感兴趣的参数的高完整性和合作重建是相当重要的，一个开放的问题。目前，还没有分析和设计理论的基础上，一个严重欠确定的数据集的操作映射。然而，也缺乏一个导航框架，可以引导车辆到更好的稀疏感测的位置。受最近非均匀采样理论突破的启发，该建议展示了网络如何利用感兴趣参数的稀疏变换进行基于相当小的观测集的合作映射。所提出的方法提供了一个答案的问题“下一个最佳位置感测”在移动的网络和引导车辆的位置，更好地压缩传感/映射。为了确保不间断的合作，它还通过提出通信感知压缩映射的基础来补充这一点。沿着这条线，它示出了如何构建反映通信不可靠性（诸如路径损耗、阴影和衰落）的现实通信目标，并将它们与压缩感知/映射目标集成。拟议中的研究是根本性的，因为它试图揭开合作移动的网络的鲁棒运行所需的最低限度的传感和通信。如果成功的话，所提出的研究将作出重大贡献的理解和优化的移动的合作网络在现实的通信环境。应急反应、探索性任务、安全和监测是必须在信息丰富的环境中有力和及时地运作的应用程序的几个例子，因此可以从拟议的工作中受益匪浅。该提案还通过与西南印第安理工学院（一所美洲原住民社区学院）和Bernalillo高中（46%的美洲原住民学生和46%的西班牙裔学生）的合作关系，对新墨西哥州的美洲原住民产生了重大的教育影响。更具体地说，它将1）有助于在西南印度理工学院建立一个控制和通信基础知识的学习平台，2）在Bernalillo高中建立一个技术/教育远程站点，3）开发一个面向上述社区大学和高中学生的网络控制课程，这些学生将与UNM的研究生合作，做与学习平台相关的项目。

The research objective of this Faculty Early Career Development (CAREER) project is to develop the foundations of sensing and navigation in mobile cooperative networks from a compressive sampling perspective. A mobile ooperative network faces an abundance of information in its environment. Since there is not enough time for direct measurement of the whole terrain, finding the fundamental minimum sensing required for high-integrity and cooperative reconstruction of the parameter of interest is considerably important and an open problem. Currently, there is no analysis and design theory for ooperative mapping based on a severely under-determined data set. onsequently, a avigation framework that can guide the vehicles to the locations better for sparse sensing is also lacking. Inspired by the recent breakthroughs in non-uniform sampling theory, this proposal shows how the network can exploit the sparse transformation of the parameter of interest for cooperative mapping based on a considerably small observation set. The proposed approach provides an answer to the question of "the next best positions for sensing" in mobile networks and guides the vehicles to the locations that are better for compressed sensing/mapping. To ensure uninterrupted cooperation, it furthermore complements this by proposing a foundation for communication-aware compressive mapping. Along this line, it shows how to build realistic communication objectives that are reflective of communication unreliability such as path loss, shadowing and fading, and integrate them with compressive sensing/mapping objectives. The proposed research is fundamental in nature as it seeks to unveil the minimum sensing and communication needed for the robust operation of cooperative mobile networks. If successful, the proposed research will make a significant contribution to the understanding and optimization of mobile cooperative networks in realistic communication environments. Emergency response, exploratory missions, security and surveillance are a few examples of the applications that have to operate in an information-rich environment robustly and in a timely manner, and can therefore benefit tremendously from the proposed work. This proposal also has a significant educational impact on the Native Americans of New Mexico through partnership with Southwestern Indian Polytechnic Institute (a Native American community college) and Bernalillo High School (with 46% Native American and 46% Hispanic students). More specifically, it will l) contribute to stablishing a learning platform for the basics of control and communications at Southwestern Indian Polytechnic Institute, 2) create a echnical/educational remote site at Bernalillo High School and 3) develop a networked control course geared towards the aforementioned community college and high school students, in which these students will team up with UNM graduate students to do projects related to the learning platform.