基于信道状态信息的参与式感知导航关键技术研究

项目名称： 基于信道状态信息的参与式感知导航关键技术研究

项目编号： No.61303233

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 王林

作者单位： 燕山大学

项目金额： 25万元

中文摘要： 无线通信技术和基于位置服务近年得到迅猛发展，高精实时的参与式感知导航是其中最主要的基础性问题之一。本项目从基本理论和实现方法两个角度研究参与式感知导航的三个基础科学问题：研究基于众包的参与式移动环境感知和协同空间构造思想的可行性问题，提出能够不依赖人工勘测、特定设备和前置学习的理论方法，通过在线学习和逐级去噪确保该导航思想在理论和实践中首次具备可行性和可扩展性；研究基于信道状态信息实时获取的高精度无线电地图构造方法，提出能够不受路径衰落、多径效应和时变干扰影响的室内导航理论和方法，有效满足无线网络导航的充分和必要条件，确保该方法在理论和实践上首次具备可行性和高效性；在此基础上，研究基于信道状态信息估计的导航策略，提出卫星导航与网络导航环境无缝自适应切换机制，避免导航路径中由于假阳/阴性误判引起的频繁切换，从而降低由不良路径信息引起的人员和移动设备开销，提高导航系统可用性和可扩展性。

中文关键词： 信道状态信息；导航技术；无线网络；设备无关被动人体检测；稀疏采样

英文摘要： With a rapid development of wireless communication technologies and location-based services recently, one fundamental research problem is the design of a real-time participatory sensing navigation (PSN) service with high fidelity. In this project, we plan to comprehensively study three key issues of PSN from both theoretical and practical two perspectives. First, we will study the feasibilities of the mobile context sensing based on the crowd-sourcing and the cooperative space construction. We target to propose a theoretical methodology that gets rid of intensive labor force, special equipment and prior context knowledge. Through an on-line learning and a gradual noise removing, we aim at ensuring the navigation to be viable in both theory and practice for the first time. Second, based on the state-of-the-arts of the wireless channel state information (CSI) acquisition and the high-fidelity and the radio map construction techniques, we plan to propose a theory and a solution that can largely battle the path-selective fading, the multi-path effect, and the timing varying nature of the wireless channel. By so doing, we can satisfy the sufficient and necessary conditions of the wireless based navigation, which guarantees that the solution possesses high efficiency in both theory and practice for the first time. Thi

英文关键词： channel state information；navigation technology；wireless networks；device-free passive human detection；sparse sampling