本文为奥地利格拉茨技术大学（作者：Dipl.-Ing. Paul Meissner）的博士论文，共175页。

位置感知是多种室内应用的关键促成因素，如物流、智能仓库或柔性生产。精确位置信息的可靠提供需要仔细融合各种传感器获取的位置相关参数，包括无线电信号的距离测量。后者是成功的户外定位系统的基础，如全球定位系统（GPS）。然而，室内环境的特点往往是密集的多径信道，起源于许多物理传播机制的叠加，这些机制是由许多空间上紧密相互作用的物体引起的。特别是对于室内定位系统，这仍然是定位误差的主要来源。然而，无线电信号在诸如墙壁等表面上的确定性反射可以进行几何建模，从而导致其路径参数与接收此类信号的设备位置之间的定义关系，从而产生与位置相关的附加信息。

这些信号路径中固有的位置相关信息是本论文的主要研究重点。几何随机信道模型允许将信号适当分解成有用的信息和不可分辨的干扰分量。虚拟锚（VAs）的概念被用于确定性多路径分量（MPCs）的几何建模，其中使用已知的平面布置图作为先验知识。实验表明，这些MPC在接收到的无线电信号中携带了很大一部分能量。本文推导了多径辅助定位的统计性能界限，将每个MPC的位置相关信息定义为信号和信道参数的函数。最重要的是，引入了信噪比（SINR），量化了每个MPC的信息量。本文提出了一种用于描述环境位置相关信息的信噪比估计方法。

基于位置相关信息，本文的研究结果允许（i）利用测量数据了解物理相关的传播现象，（i i）找到统计模型来描述它们对信号中位置相关参数的影响，以及（i i i）利用多路径可以实现良好的精度和鲁棒性能。提出了一种跟踪算法，该算法能够识别位置相关的传播现象及其各自的不确定性。利用各种情况下的实验数据，可以证明是能够建设性地使用MPC进行定位，在90%的位置估计中，始终能够保持位置误差小于5 cm。

本文的工作与现有的大多数基于无线电的室内定位的文献进行了对比，其中提出了一些方法来抵消多径的危害。通过一个实时演示系统，允许对现有和新算法进行快速和灵活的测试，并作为多径辅助跟踪的概念证明。本文的实验结果对未来室内无线应用的设计和评价具有一定的参考价值。这尤其适用于所给出的信道分析结果，为空间一致的几何随机信道模型的设计和参数化提供了指导。

Location awareness is a key enabler for a multitude of indoor applications, such as logistics, intelligent warehouses, or flexible production. The robust provision of accurate position information requires a careful fusion of location-dependent parameters acquired by various sensors, including range measurements from radio signals. The latter are the basis for successful outdoor localization systems like the Global Positioning System (GPS). However, indoor environments are often characterized by dense multipath channels. These originate from the superposition of many physical propagation mechanisms, which are caused by many spatially close interacting objects. Especially for indoor localization systems, this is still the main source of errors. However, deterministic reflections of the radio signal on surfaces such as walls can be modeled geometrically, leading to defined relationships of their path parameters with the position of an agent that is receiving such a signal and thus additional position-related information. The position-related information inherent in these signal paths is the main focus of this thesis. A geometric-stochastic channel model allows for the proper decomposition of signals into useful information and non-resolvable, interfering components. The concept of virtual anchors (VAs) is employed for the geometric modeling of deterministic multipath components (MPCs) using a known floor plan as prior knowledge. It is shown by experiments that these MPCs carry a significant part of the energy of a received radio signal. Statistical performance bounds are derived for multipath-assisted positioning, defining the position-related information of each MPC as a function of signal and channel parameters. Most importantly, a Signal-to-Interference-andNoise Ratio (SINR) is introduced that quantifies the amount of this information for each MPC. Estimation methods are presented for the SINR, which allow to characterize the position-related information of an environment. Based on the position-related information, the results presented in this thesis allow (i) to gain an understanding of the physically relevant propagation phenomena using measured data, (ii) to find statistical models to characterize their influence on the position-related parameters in the signals, and (iii) to show the excellent accuracy and robustness that can be achieved by exploiting multipath. Tracking algorithms are proposed that can be made aware of the positionrelevant propagation phenomena and their respective uncertainty. Using experimental data from various scenarios, this is shown to be the key factor enabling the constructive use of MPCs for positioning, consistently leading to position errors below 5 cm for 90 % of the estimates. The work in this thesis is in contrast to most existing literature on radio-based indoor positioning, in which methods are presented to counteract the performance impairments of multipath. One outcome is a real-time demonstration system that allows for fast and flexible testing of existing and new algorithms and serves as a proof-of-concept for multipath-assisted tracking. The experimental results in this thesis are valuable for the design and evaluation of future indoor wireless applications. This is especially true for the presented results on channel analysis, which give guidelines for the design and parametrization of spatially consistent geometric-stochastic channel models.

1 引言

2 几何/随机环境与信号建模

3 多径辅助定位（位置相关信息）的性能界限

4 信道分析：估计位置相关信息

5 多径辅助跟踪算法

6 结论与展望

7 其它相关讨论

8 其它研究结果

9 相关论文

附录A 室内信道测量的描述

附录B 楼层平面的不确定性建模 

下载英文原文地址：

http://page3.dfpan.com/fs/alcjb2217291d634d25/ 

更多精彩文章请关注微信号：