NeTS: Cognitive Networking of the Oceans: Localization and Tracking Fundamentals

NeTS：海洋认知网络：定位和跟踪基础知识

• 批准号: 1704813
• 负责人: Stella Batalama
• 金额: $ 50万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2017-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1704813&HistoricalAwards=false
• 关键词: NeTS; Cognitive; Networking; Oceans; Localization

Undersea wireless communications and networking has a wide range of potential scientific, commercial, and military applications, but is still a daunting task due to the very nature of the water propagation medium. Fundamental to the success of undersea communications is robust localization and tracking to support position-aware data routing and autonomous navigation in the GPS-less oceanic environment. Current state-of-the-art approaches for undersea localization and tracking consider expensive, power-intense inertial measurement sensors, geophysical-based imaging, and acoustic signaling techniques. However, long propagation delays, Doppler effects due to water movement, and the highly dynamic multipath nature of the undersea environment result in significant errors and outliers in acoustic and imaging measurements. This project aims to significantly advance (five-fold in precision) the state of the art in 3D-passive undersea acoustic localization by providing novel algorithmic solutions to the problem of estimating the angle of arrival of undersea propagating signals in the presence of potentially faulty measurements. The algorithms will then be embedded in in-house-developed programmable underwater acoustic modems to form an experimental four-node network for evaluation and demonstration. Localization capabilities will be demonstrated in communication, command and control application scenarios for remote wireless navigation and surveillance. The project will integrate research and education at all University-degree levels by establishing cross-listed graduate/undergraduate courses on undersea acoustic localization and its applications and activities to reach out to groups of middle and high-school students. Technology transfer activities in this field will be also pursued.The project pursues a paradigm shift in how signal Direction-of-Arrival (DoA) estimation is carried out over undersea acoustic links by deviating from the familiar L2-norm-subspace decomposition theory and its variants and considering, for the first time, L1-norm signal subspace decomposition. Motivated by the resistance of L1-norm-derived subspaces against outliers and/or data corruption and the recent computational advances in the field, this project will employ novel L1-norm maximum-projection principal-component analysis of the antenna array measurements to design a novel, outlier- Doppler- and multipath-resistant DoA estimation method for undersea acoustic networks. L1-norm localization and tracking will support position-aware data routing and autonomous navigation applications in the GPS-less oceans under occasional severe dynamic signal scattering and path loss.

海底无线通信和网络具有广泛的潜在科学、商业和军事应用，但由于水传播介质的性质，仍然是一项艰巨的任务。海底通信成功的基础是鲁棒的定位和跟踪，以支持位置感知数据路由和在无GPS的海洋环境中的自主导航。当前用于海底定位和跟踪的最先进的方法考虑昂贵的、功率密集的惯性测量传感器、基于光电的成像和声信号技术。然而，长的传播延迟，由于水的运动多普勒效应，以及高度动态的多路径性质的海底环境的结果在声学和成像测量的重大错误和异常值。该项目旨在通过提供新的算法解决在存在潜在错误测量的情况下估计海底传播信号到达角的问题，大大推进（精度提高五倍）三维被动海底声学定位的最新技术水平。这些算法将嵌入到内部开发的可编程水声调制解调器中，形成一个实验性的四节点网络，用于评估和演示。定位能力将在远程无线导航和监视的通信、指挥和控制应用场景中得到展示。该项目将通过建立有关海底声学定位及其应用和活动的交叉列出的研究生/本科生课程来整合所有大学学位级别的研究和教育，以覆盖初中和高中学生群体。该项目力求在如何通过海底声学链路进行信号到达方向估计方面实现范式转变，方法是偏离熟悉的L2范数子空间分解理论及其变体，并首次考虑L1范数信号子空间分解。受L1范数导出子空间对离群值和/或数据损坏的抵抗力以及该领域最近的计算进展的启发，该项目将采用新颖的天线阵列测量的L1范数最大投影主分量分析来设计一种新颖的、抗离群值-多普勒和多径的海底声学网络DoA估计方法。L1范数定位和跟踪将支持在偶尔严重的动态信号散射和路径损耗下的无GPS海洋中的位置感知数据路由和自主导航应用。