无线传感器网络混合定位技术研究

在大规模复杂无线传感器网络中往往采用多种节点定位技术,在此结合现有无线传感器定位技术的现状,提出了一种混合定位技术以实现不同定位方法之间的互补。一方面利用RSSI定位弥补TDOA定位覆盖范围小的缺点;另一方面将测距信息引入到非测距定位DV—Hop算法中,用RSSI测距模型来提高DV-Hop算法中定位节点与信标节点间有效距离的精度。实验结果表明,该混合定位技术实现了TDOA,RSSI以及DV-HOP等定位技术的融合,有效地提高了复杂大规模无线传感器网络的节点定位精度。     

一种基于多天线簇的新型LTE室内定位系统

随着移动互联网业务的迅速发展,位置服务需求越来越多样化,定位技术也变得越来越重要.LTE(long term evolution)室内蜂窝网络可以解决GPS(global positioning system)信号无法进入室内的问题,从而提供高精度的位置服务.LTE室内定位需要不同基站之间进行精确同步,这给室内网络部署带来了新的挑战.针对上述问题,提出了一种基于多天线簇的LTE新型无线定位系统,通过上行探测参考信号(sounding referencesignal,SRS)获取信号到达时间差(time difference of arrival,TDOA).该方法不需要簇间同步,可有效降低网络部署难度.其次,针对此系统设计了一种新的TDOA定位算法,可支持灵活的天线簇配置.最后,通过仿真及实验验证了该定位系统及算法的有效性,实验结果表明可实现米级室内定位精度.     

A statistical modeling approach to location estimation

Some location estimation methods, such as the GPS satellite navigation system, require nonstandard features either in the mobile terminal or the network. Solutions based on generic technologies not intended for location estimation purposes, such as the cell-ID method in GSM/GPRS cellular networks, are usually problematic due to their inadequate location estimation accuracy. In order to enable accurate location estimation when only inaccurate measurements are available, we present an approach to location estimation that is different from the prevailing geometric one. We call our approach the statistical modeling approach. As an example application of the proposed statistical modeling framework, we present a location estimation method based on a statistical signal power model. We also present encouraging empirical results from simulated experiments supported by real-world field tests.     

移动终端的定位跟踪系统研究与实现

定位跟踪技术是指通过特定的定位技术来获取移动手机或终端用户的位置信息(经度、纬度坐标等),并且在电子地图上对跟踪终端的位置进行标注的技术或服务。该系统综合使用了GPS定位技术、WEBGIS、GSM通信网络、GPRS无线分组技术、中间件等技术实现了对移动的终端进行定位跟踪的功能,实现对终端人员的实时跟踪和位置信息的动态管理。移动定位跟踪技术的主要应用场所有以下4种:追踪服务、信息服务、安全服务和付帐服务。     

多基站GPS差分定位在航标遥测遥控中应用

为了提高航标遥测遥控系统中GPS单频伪距定位精度,提出多基站GPS差分伪距定位方法。该方法以单基站定位为基础,先通过单基站伪距改正数消除对流层、电离层的影响,再根据基站与测量站之间的距离关系建立基于距离的线性内插模型,从而得到综合改正数。利用综合改正数修正测量站的数据,提高了定位精度。实验结果表明,此方法能够有效地减少基站与测量站之间距离带来的误差,大大提高了航标遥测遥控的定位精度。     

Database Correlation Method with Error Correction for Emergency Location

The constantly growing number of mobile terminal users increases also the number of mobile originated emergency calls. In the United States mobile terminal location in case of an emergency call was mandated with stringent accuracy requirements by Federal Communications Commission (FCC) in 1996. Since July 2003 emergency call location is required also in the European Union (EU), but contrary to the US, without accuracy limits. The global positioning system (GPS) offers high location accuracy, but the density of GPS-capable terminals is very low. Thus, to be able to provide location estimations for all mobile originated emergency calls nationwide, techniques based on cellular network are preferred. In many cases, however, conventional techniques cannot provide sufficient accuracy. This is typical especially for urban areas, where obstacles in signal propagation path degrade location estimation. In urban areas the mobile terminal user density is high and a substantial part of urban emergency calls are mobile originated requiring accurate location estimation. In this paper, we propose a method for emergency call location in urban areas. This database correlation method (DCM) is complemented by error correction method (ECM) developed in the frame of the EU IST project cellular network optimization based on mobile location (CELLO) [http://www.telecom.ntua.gr/cello/]. In performance evaluations DCM has proven to offer sufficient urban accuracy of 44 m in GSM field trial and 25 m in UMTS simulations. The ECM has been tested and proven to ease the implementation of DCM.     

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.

Chan定位算法与TDOA估计精度的关系

在基于TDOA（到达时间差）的定位算法中,Chan方法由于其独特的优势得到广泛应用,但如何估计Chan定位算法所需的时延估计精度暂时没有明确的函数表达式。针对Chan定位算法,推导了该算法定位估计误差与定位参数（TDOA）估计精度之间的函数关系。给出了推导的具体步骤和函数关系的表达式,分析了该表达式所具有的物理意义。在移动台无线定位系统的设计过程中,根据所需的定位精度,通过该表达式可以直接计算出系统所必须的最小时延估计精度。     

基于ZigBee的城市公交车定位系统设计

利用无线传感器单片机CC2431和CC2430设计了一个基于ZigBee的公交车无线定位系统。传统的定位都是采用GPS或者GPRS的定位。GPS定位系统设计简单,可以使用免费的定位卫星资源,但是移动台到控制中心的数据传送需要借助其它网络资源;GPRS定位是基于移动蜂窝式通信的定位,使用现有的移动网络,但是带宽低,不利于突发事件的快速处理。本文设计的Zigbee的无线定位系统基于无线单片机CC2431[1],利用CC2431自带的RSSI定位引擎[2],再运用无线自组网[3]进行定位并向控制中心传送定位信息。该系统设计简单,定位精确度高,设备成本低廉,适合现代化城市的公交车系统智能管理。     

基于扩展卡尔曼滤波的非视距误差消除算法

在蜂窝网无线定位中,到达时间(TOA)或到达时间差(TDOA)中的非视距(NLOS)误差会导致移动台的位置估计出现较大偏差.为了减轻NLOS误差的影响,提出了一种基于扩展卡尔曼滤波(EKF)的非视距误差消除算法.算法通过引入一个NLOS转换因子改进EKF的迭代过程,消除NLOS误差对定位估计的影响.计算机仿真结果表明,在NLOS环境下定位精度的提高是显著的.     

传感网络中基于移动信标的网格扫描定位算法

节点定位是传感网络最基本的技术之一,对此提出一种基于移动信标的网格扫描定位算法(Mobile Beacon Grid-Scan,MBGS)。该算法在网格扫描定位算法基础上,利用一个移动信标巡航整个传感区域,产生大量的虚拟信标,提高网络信标覆盖率,然后普通节点利用这些信标信息减小其可能区域(Estimative Rectangle,ER),并把新可能区域网格坐标质心作为其最新估计坐标。仿真结果表明,与Bounding Box、质心定位算法以及传统的网格扫描定位算法相比,MBGS定位方法的定位精度更高,算法性能更加稳定。     

GSM Mobile Station Location Using Reference Stations and Artificial Neural Networks

In this paper we present a novel approach to the automatic GSM mobile station location. The approach is based on measurement of radio signal strengths from a number of the neighboring base stations (antennas) and estimation of the mobile station position using trained artificial neural network (ANN) models. First, we present an improved version of our previous positioning back propagation (BP) ANN multi-level perceptron (MLP) model that further improves positioning accuracy. Then, we extend the MLP primary ANN model by introducing correctional factors obtained from a number of reference stations with known positions. Two new models with the improved location accuracy, both aimed at real-time application, are presented. The first model is using differential range to improve the estimated location of the mobile station. The second is using small-scale secondary neural networks trained with data obtained from reference stations, in addition to the primary ANN, to correct location accuracy.     

小波分析法解决无线定位跟踪问题

无线定位中,信号的非视距传播（NLoS）很大程度上决定了移动台的定位精度,而小波分析理论在信号处理中有较为明显的优点,提出了一种在蜂窝网络中非视距环境下对移动台（MS）的定位及跟踪算法。利用小波变换对信号的分解和重构,实现了对TDOA测量值误差的修正,再利用经典Chan算法对移动台位置进行估计,配合相应的距离门限值对移动台的位置进行跟踪定位。仿真结果表明,该算法能够有效地实现对移动台位置的静态定位和动态跟踪,并明显优于同等环境下经典算法的仿真结果,有效提高了定位精度。     

Location Estimation via Support Vector Regression

Location estimation using the global system for mobile communication (GSM) is an emerging application that infers the location of the mobile receiver from multiple signals measurements. While geometrical and signal propagation models have been deployed to tackle this estimation problem, the terrain factors and power fluctuations have confined the accuracy of such estimation. Using support vector regression, we investigate the missing value location estimation problem by providing theoretical and empirical analysis on existing and novel kernels. A novel synthetic experiment is designed to compare the performances of different location estimation approaches. The proposed support vector regression approach shows promising performances, especially in terrains with local variations in environmental factors     

融合反距离加权和矩阵填充的位置指纹库构建

为解决位置指纹定位在离线阶段构建位置指纹库时耗费的人力和时间成本较大,构建指纹库效率低和利用空间插值法构建的指纹库精度不高的问题,提出了一种融合反距离加权和矩阵填充的位置指纹库构建算法。该算法仅需人工采集定位区域内少量参考点的接收信号强度值用作信标点指纹信息,结合反距离加权算法特性计算出次信标点指纹信息,根据位置指纹库数据矩阵的低秩性,应用奇异值阈值矩阵填充算法构建出位置指纹数据库。仿真实验结果表明,所提算法有效降低了矩阵填充算法构建位置指纹库所需的人工和时间成本,构建出的位置指纹库定位性能优于反距离加权和克里金空间插值法,接近传统人工采集法,显著地提高了位置指纹库的构建效率。     

混合无线定位技术的应用研究

无线定位技术在现代社会中发挥着重要的作用。文中首先描述基于GPS、蜂窝网络和RFID的3种典型无线定位技术的原理,分析了各自的特点,并介绍了混合无线定位技术在手机定位和智能交通管理中的应用实例。研究表明,混合无线定位技术,综合了多种无线定位技术的优点,能有效提高定位准确性和可靠性,是无线定位技术发展的趋势。     

基于蜂窝网的抗NLOS定位算法研究

非视距（NLOS）误差是蜂窝网定位系统的主要误差源，直接影响基于蜂窝网络的定位系统的推广和应用。针对提高抗NLOS定位精度算法的研究，分别从NLOS传播特性、NLOS鉴别和NLOS抑制算法等几个方面进行了详细的分析和讨论，综述了该领域的最新研究进展，并提出了自己的观点。     

Tunnel lane‐positioning system for autonomous driving cars using LED chromaticity and fuzzy logic system

Currently, studies on autonomous driving are being actively conducted. Vehicle positioning techniques are very important in the autonomous driving area. Currently, the global positioning system (GPS) is the most widely used technology for vehicle positioning. Although technologies such as the inertial navigation system and vision are used in combination with GPS to enhance precision, there is a limitation in measuring the lane and position in shaded areas of GPS, like tunnels. To solve such problems, this paper presents the use of LED lighting for position estimation in GPS shadow areas. This paper presents simulations in the environment of three‐lane tunnels with LEDs of different color temperatures, and the results show that position estimation is possible by the analyzing chromaticity of LED lights. To improve the precision of positioning, a fuzzy logic system is added to the location function in the literature [1]. The experimental results showed that the average error was 0.0619 cm, and verify that the performance of developed position estimation system is viable compared with previous works.     

RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers

Solutions for indoor tracking and localization have become more critical with recent advancement in context and location-aware technologies. The accuracy of explicit positioning sensors such as global positioning system (GPS) is often limited for indoor environments. In this paper, we evaluate the feasibility of building an indoor location tracking system that is cost effective for large scale deployments, can operate over existing Wi-Fi networks, and can provide flexibility to accommodate new sensor observations as they become available. This paper proposes a sigma-point Kalman smoother (SPKS)-based location and tracking algorithm as a superior alternative for indoor positioning. The proposed SPKS fuses a dynamic model of human walking with a number of low-cost sensor observations to track 2-D position and velocity. Available sensors include Wi-Fi received signal strength indication (RSSI), binary infra-red (IR) motion sensors, and binary foot-switches. Wi-Fi signal strength is measured using a receiver tag developed by Ekahau, Inc. The performance of the proposed algorithm is compared with a commercially available positioning engine, also developed by Ekahau, Inc. The superior accuracy of our approach over a number of trials is demonstrated.     

利用数字移动电话网建车辆定位服务网的探讨

从实际应用的角度,分析利用ＧＳＭ网建立ＧＰＳ车辆安全服务系统的优势与特点,对ＧＳＭ／ＧＰＳ车载设备的设计与产品化、ＧＳＭ／ＧＰＳ服务网及未来的产品和系统发展方向提出了看法。