PECASE: Compressive Cooperative Sensing and Navigation in Mobile Networks

这个教师早期职业发展（Career）项目的研究目标是从压缩采样的角度发展移动合作网络中传感和导航的基础。移动运营网络面临着环境中丰富的信息。由于没有足够的时间对整个地形进行直接测量，因此找到对感兴趣的参数进行高完整性和协作重建所需的基本最小感知是相当重要的，也是一个悬而未决的问题。目前还没有基于严重欠确定数据集的协同映射的分析和设计理论。因此，缺乏一种能够更好地引导车辆到稀疏感知位置的导航框架。受非均匀抽样理论最新突破的启发，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。所提出的方法为移动网络中“下一个最佳感知位置”的问题提供了答案，并引导车辆到达更适合压缩感知/映射的位置。为了确保不间断的合作，它通过提出通信感知压缩映射的基础进一步补充了这一点。沿着这条线，它展示了如何构建反映通信不可靠性（如路径损失、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。拟议的研究本质上是基础性的，因为它寻求揭示协作移动网络稳健运行所需的最小传感和通信。如果研究成功，将对理解和优化现实通信环境下的移动协作网络做出重大贡献。应急反应、探索任务、安全和监视是必须在信息丰富的环境中可靠和及时地运行的应用程序的几个例子，因此可以从拟议的工作中获得巨大好处。该提案还通过与西南印第安理工学院（美国原住民社区学院）和伯纳利略高中（有46%的美国原住民和46%的西班牙裔学生）的合作，对新墨西哥州的美国原住民产生了重大的教育影响。更具体地说，它将1)在西南印度理工学院建立一个控制与通讯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)针对上述社区大学和高中学生开发一个网络控制课程，这些学生将与新墨西哥大学的研究生合作，完成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.