基于CFR虚拟阵列天线的AOA室内定位

准确地估计信号的到达角（Angle Of Arrival,AOA）为实现在室内高精度定位提供了可能,为了能够准确地估计室内多径信号的AOA,并提取出直射路径的AOA信息进行定位,本文提出一种利用信道频率响应信息（Channel Frequency Response,CFR）扩展阵列天线的亚米级室内定位系统.首先,采集CFR信息进行AOA和信号到达时间（Time Of Arrival,TOA）的联合估计;其次,提出了一种基于AOA和TOA二维聚类信息的直射路径识别算法;另外,还提出了可视环境（Line Of Sight,LOS）以及非可视环境（Non Line Of Sight,NLOS）的识别算法,可以准确的判断出当前接收机相对发射机是处于LOS还是NLOS环境;最后,利用现有的三天线Wi-Fi设备在室内进行了测角以及定位测试,实验结果表明本文提出的定位系统在室内LOS和NLOS环境下分别可以达到中值误差为0.8m,1.3m的定位精度,可用于室内高精度定位.     

On the Cramer-Rao lower bound for RSS-based positioning in wireless cellular networks

An accurate position of a mobile user's location is substantial in wireless cellular networks with respect to location based services (LBS) implementation. Among the available parameters used to estimate a desired location, low cost measurement of received signal strength (RSS) makes it suitable for outdoor and indoor positioning. Our aim here is to look at the performance of a theoretically optimal user's position estimator. We examine the Cramer-Rao lower bound (CRLB), which sets the lowest variance of any unbiased estimator. Due to the oversimplification with respect to reliance on detailed cognizance of environment, we deploy theoretical free-space and empirical COST-231-Hata, Stanford University Interim (SUI) and ECC-33 path loss models that are dominantly used in real scenarios aiming to form the system model equations. The findings show that the CRLB on estimation precision depends on the underlying path loss exponents (PLE) and the relative positions of the mobile and base stations. The calculated bounds provide a benchmark against which it is possible to evaluate different positioning algorithms, techniques and estimators relying on the specified path loss models.     

Heuristics-based indoor positioning systems: a systematic literature review

Context: Many heuristics-based indoor positioning approaches have been developed to enhance positioning estimation. However, there is no comprehensive survey of these heuristics information and methods. Objective: The main objective of this study is to provide a holistic view and an in-depth analysis of what heuristics information and methods have been used, their general achievements and limitations. This study aims to provide a comprehensive summary to facilitate further research on indoor positioning heuristics. Method: We conducted a systematic literature review (SLR) on indoor positioning heuristics. Results: Ninety-three (93) primary studies were selected. We found two general types of heuristics information and four primary heuristics methods, which we summarised in this paper. We also found that many of these positioning heuristics are tested in experimental settings only. Some heuristics claim practical applications but are not tested for the challenging and typical indoor environments. Conclusion: Most existing heuristics information and methods rely on the assumptions that may not be true in real life environment, hence limiting the usefulness of the positioning outcomes. Based on the analysis of this SLR, we propose two research directions to enhance positioning estimation.     

一种超宽带与惯导融合的LSTM室内定位算法

针对复杂环境下的室内高精度定位需求,提出了一种超宽带和惯导融合定位方案.结合位置估计过程可被划分为时间序列预测问题的特点,提出了一种基于长短时记忆(Long Short Term Memory,LSTM)网络的联合定位算法,并对其总体架构设计、数据预处理方法、网络结构设计、模型训练方法进行了研究.在此基础上,通过仿真和...     

多照明区域协作的室内可见光定位

考虑室内存在障碍物遮挡及背景光和反射光干扰 较强的实际定位场景,提出了一种基于多照明区域 协作的LED可见光室内定位方法。本文方法引入多照明区域联合定位思想,利用分布于室内 不同区域的LED 发出的参考信号估计定位节点到各LED的信号传输时间差,构造协作定位距离估计目标函数 ,并通过非线 性最小二乘(NLLS)算法获得定位目标的位置估计。将提出的定位算法在10m×3m的空间区域中进行定位仿 真,在5W LED照明、双区域协作条件下,获得了平均定位误差7.41 cm的定位精度。结果表明:提出的协 作算法不仅提高了室内定位精度和系统应用的普适性及鲁棒性,而且有效地解决了室内可见 光定位存在的遮挡效应;此外,对动态定位追踪也有一定的效果。     

基于多LED的高精度室内可见光定位方法

针对可见光室内定位问题,该文基于接收信号强度(RSS)定位技术,提出一种利用多个LED发射端实现室内定位的方法,即MLED-RSS定位算法。该方法在充分考虑LED拓扑结构对定位性能影响的基础上,利用部署在室内的多个LED,合理选择其中3个LED作为发射节点,采用改进的三边定位法获得定位目标位置信息。定位算法可以有效地解决可见光定位存在的遮挡效应。仿真实验表明,MLED-RSS算法可以实现高定位精度。     

A Novel Wireless Positioning System for Seamless Internet Connectivity based on the WLAN Infrastructure

Nowadays, several positioning systems are available for outdoor localization, such as the global positioning system (GPS), assisted GPS (A-GPS), and other systems working on cellular networks, for example, time difference of arrival (TDOA), angle of arrival (AOA) and enhanced observed time difference of arrival (E-OTD). However, with the increasing use of mobile computing devices and an expansion of wireless local area networks (WLANs), there is a growing interest in indoor wireless positioning systems based on the WLAN infrastructure. Wireless positioning systems (WPS) based on this infrastructure can be used for indoor localization to determine the position of mobile users. In this paper, we present a novel wireless positioning system, based on the IEEE 802.11b standard, using a novel access point (AP) with two transceivers to improve the performance of WPS in terms of accuracy of the location estimation and to avoid service connectivity interruption. In our proposed system, the novel AP uses the second transceiver to find information from neighboring mobile stations (STAs) in the transmission range and then sends information in advance to associated APs, which estimate the location of the STA based on an internal database. We also use a TDOA technique to estimate the location of the STA when there is not enough information in the database (in this case, the STA moves into a new area where the system has not run the calibration phase). Using TDOA, the database can be generated and updated automatically. The initial results from our simulations show that the proposed system provides higher accuracy of location estimation than other related work and does not interrupt the Internet connection for end users in contrast with other proposed schemes.

Exploring the limits of PDR-based indoor localisation systems under realistic conditions

ABSTRACT

Pedestrian Dead Reckoning (PDR) plays an important role in many (hybrid) indoor positioning systems since it enables frequent, granular position updates. However, the accumulation of errors creates a need for external error correction. In this work, we explore the limits of PDR under realistic conditions using our graph-based system as an example. For this purpose, we collect sensor data while the user performs an actual navigation task using a navigation application on a smartphone. To assess the localisation performance, we introduce a task-oriented metric based on the idea of landmark navigation: instead of specifying the error metrically, we measure the ability to determine the correct segment of an indoor route, which in turn enables the navigation system to give correct instructions. We conduct offline simulations with the collected data in order to identify situations where position tracking fails and explore different options how to mitigate the issues, for example through detection of special features along the user’s path or through additional sensors. Our results show that the magnetic compass is often unreliable under realistic conditions and that resetting the position at strategically chosen decision points significantly improves positioning accuracy.     

Deployment of RSS-Based Indoor Positioning Systems

Location estimation based on Received Signal Strength (RSS) is the prevalent method in indoor positioning. For such positioning systems, a massive collection of training samples is needed for their calibration. The accuracy of these methods is directly related to the placement of the reference points and the radio map used to compute the device location. Traditionally, deploying the reference points and building the radio map require human intervention and are extremely time-consuming. In this paper we present an approach to reduce the manual calibration efforts needed to deploy an RSS-based localization system, both when using only one RF technology or when using a combination of RF technologies. It is an automatic approach both to build a radio map in a given workspace by means of a signal propagation model, and to assess the system calibration that best fits the required accuracy by using a multi-objective genetic algorithm.     

OFDM-UWB系统的自适应联合信道估计算法

提出了一种新的MB-OFDM-UWB自适应联合信道估计算法,该算法首先对基于DFT的信道估计算法进行改进,使其能自适应的调整滤波窗口的大小。然后利用改进后的算法与梳状导频估计相结合。算法的优点在于能根据不同的信道的统计特征,自适应调整滤波器窗口的大小,从而减少了噪声对信道估计的影响,并保留了梳状导频估计能快速跟踪信道变化的特性。仿真结果表明,该算法能很好地适用于UWB室内信道。     

Analysis and Performance of a Smart Antenna for 2.45-GHz Single-Anchor Indoor Positioning

This paper presents the theoretical analysis and the experimental evaluation of a new switched beam antenna designed to operate at 2.45 GHz. The antenna enables direction of arrival estimation using six directional planar elements arranged to form a platonic solid geometry. It also supports polarization diversity, and it is suitable for single-anchor indoor positioning applications. We adopt the CramÉr–Rao bound to study the estimation accuracy of the proposed antenna in absolute 2-D target positioning using received signal strength measurements. First, we describe the design principles for the radiators, we provide an extensive characterization of the switched antenna prototype, and we discuss positioning applications. We then report experimental data that support the results of the theoretical analysis and show consistency between theoretical expectation and the measurements. Finally, we discuss results from proof-of-concept operative indoor positioning example, showing an average localization error as low as 1.7 m.      

Optimizing event coverage in theme parks

Theme parks can be modeled as geographical areas where large crowds of people move among different attractions. The operators of a theme park are interested in quickly and efficiently handling events occurring at various locations in the park. We propose a model which deploys a wireless network with mobile sinks to facilitate event coverage. The event coverage problem can be divided into two sub-problems: the static problem of mobile sink positioning and the dynamic problem of event handling decisions of the mobile sinks. For the mobile sink positioning problem we propose two strategies: crowd density based probability estimation and hot-spot based probability estimation. For the event handling decision problem, we propose an approach which represents movement opportunities in the park as a graph with dynamically changing weights, and searches for the shortest path in this dynamic graph. The proposed approaches are simulated on scenarios which model the movement of the visitors using two sophisticated human mobility models.     

室内无线传感器网络链路质量特征研究

首先分析了室内无线传感网络链路特点及传统链路质量特征描述存在的问题,指出了人类活动对室内无线传感器网络链路质量的显著影响。其次提出并描述了人体室内运动模型,在此基础上提出了人体运动条件下室内无线传感器网络有效区域,过渡区域和无效区域的估计方法,给出了上述区域中人体运动造成的数据接收成功率下降的理论界限。通过构造人体运动条件下干扰实验案例,分析了上述估计方法的性能。     

Modeling of the TOA-based distance measurement error using UWB indoor radio measurements

Time of arrival (TOA) estimation used with ultra wideband (UWB) transmission is currently the most popular technique for accurate indoor geolocation. Due to severe indoor multipath conditions, these techniques often suffer from significant inaccuracy in location estimation. In this paper, we introduce a model for the error in estimated distance as measured from the estimated TOA of the direct path (DP) in a typical multipath indoor environment. The TOA estimation error has two components, (1) the errors caused by the multipath dispersion affecting any signal path and (2) the errors caused by undetected direct path (UDP) conditions. The statistical behavior of this error is also a function of the system bandwidth. The empirical data from UWB indoor measurements in an office building are used to design a model for the distance measurement error. This model relates the behavior of the two components of the TOA estimation error to the bandwidth of the system.     

Survey of Wireless Indoor Positioning Techniques and Systems

Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.     

室内定位技术应用分析研究

本文阐述了室内定位技术的应用场景、实现原理和面临的问题，介绍了典型的室内定位系统，通过对不同技术优劣的比较和对室内定位技术发展趋势的分析，得出如下的结论：现阶段室内定位解决方案要综合考虑用户需求、环境特性、各种定位技术的优劣进行设计，融合多种技术提高性能。未来室内定位技术的发展将会向着融合多种技术的分米级广域无缝室内外定位的目标前进。     

基于微气压传感器的室内行人高度估计方法

针对当前气压传感器解算高度存在误差随时间累积的问题,提出了一种基于微气压传感器的室内行人高度估计新方法。该方法结合微气压传感器的输出高度值,对多个相邻时间内的高度值进行合理性判断,并结合室内行人运动状态对高度变化进行约束,使得解算的高度符合室内行人运动规律。通过电脑采集MS5611微气压传感器数据进行仿真验证,结果表明:该方法能够有效地对高度误差进行修正,相较于微气压传感器直接解算的高度,该算法解算的高度更贴合实际情况,解算轨迹也更接近真实轨迹,轨迹的平均闭环误差从1.9%D下降至0.07%D。该算法有效地提高了室内行人高度估计的定位精度,在室内行人三维定位领域具有一定的工程应用价值。     

高精度室内可见光定位算法

针对目前室内定位算法精度不高、实现复杂等问 题,提出了一种基于白光LED的可见光室内定位方 法。首先利用由室内不同LED发出的定位参考信号到达定位终端的时间差(TDOA )的测量估计,得 到定位终端到达两个LED的传输距离之差,以此构造距离估计目标函数,然后采用有约束非 线性规划算法得到 定位终端的位置坐标,从而有效地解决了室内噪声环境中常规TDOA定位算法不收敛或误差偏大的问题。 同时,为了进一步优化定位性能,将距离信息引入加权因子中,提出了质心加权混合定位算 法。将提出的 定位算法在5m×5m×3m的空间区域中进行了仿真实验,同时考虑噪声因素的影响,结果 表明,提出的距离 估计目标函数法在信噪比(SNR)为2dB的条件下可以达到平 均5cm的定位误差,采用质心加权处理后平均定位误 差仅为3cm,有效地提高了室内定位精度和系统应用的普适性及鲁棒性。     

Novel fingerprinting mechanisms for indoor positioning

As wireless communications and microelectronic technology rapidly develop, diverse applications and services based on smart handheld devices have drawn the attention of researchers. The popularity of Indoor Location Based services and applications has also gradually increased. Therefore, how to improve indoor positioning accuracy becomes a very important issue. Although indoor positioning has been performed using various techniques in recent years, the computational complexity of ensuring positioning accuracy and positioning is an unsolved problem. Current indoor positioning systems typically use only the receiver or the transmitter to obtain the reference point data, and only the K‐Nearest Neighbors (KNN) or Trilateration algorithm is used to perform positioning. Therefore, positioning accuracy is limited by the use of reference point data from a single source and by the positioning algorithm used. The Novel Fingerprinting Mechanisms (NFM) indoor positioning system proposed in this study, however, uses both the receiver and transmitter to obtain positioning data and employs six positioning mechanisms to improve the current positioning accuracy. The experimental results show that the average error distance is 1.18 m in the NFM indoor positioning system. That is the system outperforms both KNN and Trilateration systems, which have average error distances of 1.35 m and 2.23 m, respectively. This study proves that the positioning accuracy is actually improved. Copyright © 2015 John Wiley & Sons, Ltd.     

基于WiFi的自适应匹配预处理WKNN算法

针对基于接收信号强度（Received Signal Strength,RSS）的WiFi室内定位技术中,传统加权K邻近（Weighted K-nearest Neighbor,WKNN）算法不能自适应获取WLAN中有效接入点（Acess Point,AP）且参考点匹配准确度不高的问题,本文提出了自适应匹配预处理WKNN算法。该算法中每个实时定位点自适应地根据网络状况对AP的RSS均值由大到小排序,然后选择RSS均值较大的前M个AP,与参考点中对应的M个AP一起参与匹配预处理计算,从而优化了传统的指纹定位算法。同时将室内定位和室内地图相结合,使参考点和定位结果直观地展示在地图上,并通过使用地图数据大幅度简化了离线训练过程。此外,本文设计并实现了基于Android平台的室内定位系统,通过该系统验证了本文所提算法在单点定位和移动定位中的有效性。实验结果表明,该算法可获得30%以上的定位误差改善,有效提高了定位精度和定位稳定性。