用于WLAN室内定位的PCA聚类算法

在WLAN室内定位系统中,针对接收信号强度(RSS)的时变特征降低室内定位精度的问题,提出一种基于主成分分析(PCA)白化RSS的聚类算法,该算法首先对信号强度进行PCA白化处理,去除RSS信息的相关性,提高聚类中心的可靠性和合理性,然后通过K-means聚类方式对RSS信息进行聚类,能够有效地提高聚类精度,以此来提高定位精度.实验结果表明,该算法相比于没有经过PCA的传统聚类算法,能够使定位误差在2m内的概率提高44.8％,性能更优良.     

基于WLAN的室内定位技术研究

文章以WLAN室内定位系统为研究对象,采用理论结合实际的方法,从数据库中获得RSSI序列,将之与指纹库的信息进行比对,最终获得了定位终端的位置,同时总结了定位系统的缺陷以及未来的发展方向。     

基于偏度-峰度检验的无线局域网室内定位算法

针对室内无线局域网环境下接收信号强度(RSS,received signal strength)样本总体分布不一致而产生较大定位误差的问题,提出了一种基于偏度-峰度检验的室内定位算法.利用偏度-峰度检验法检验RSS样本是否来自正态总体,接受零假设的样本用正态分布近似其总体分布,拒绝零假设的样本用核函数估计其概率密度.实验结果表明提出算法的定位精度比传统算法提高15％以上,而且在相同的定位精度下,能明显降低离线阶段的工作量.     

一种基于位置指纹的室内WLAN定位方法

针对室内信号时变性导致定位不准的问题,提出了一种改进的3阶段位置指纹定位法。采样阶段,将采集信号的坐标、方位、接收信号强度的高斯分布及其对应的无线接入点等信息存储在数据库中生成位置指纹;在校正阶段中,利用参考点间信号强度的关联性信息,使用局部加权线性回归法,计算出一些虚拟点的信号强度;最后是线上实时定位阶段。通过与传统的加权K最邻近算法、直方图和联合聚类等3种定位方法相比较,该算法在同样的场景下可以取得更好的定位精度。     

基于RFID的室内定位系统研究

RFID技术是一种全新的非接触自动识别技术,是物联网技术进行用户识别和定位处理的前提。文章在简单介绍RFID技术的基础上对基于到达时间、基于到达时间差、基于到达角、基于到达信号强度和基于相位的定位技术进行了分析。分析结果表明基于相位信息的定位系统相比其他系统而言,对硬件要求不高,可操作性强,有较强的抗干扰能力,具有较高的实用价值。     

一种基于无源射频识别标签的消防员室内定位系统

消防员在地下建筑、无窗建筑、大型建筑物内,执行火情控制与人员搜救时,不可避免会遇到浓烟、黑暗、高温、陌生等情况,因此就需要精确的室内定位系统支持,已有的室内定位技术无法满足定位精度和长期部署的需求.本文提出了一种基于无源射频识别（RFID）标签的消防员室内定位系统,通过在消防员头盔内安装可变功率的RFID读写器,并将建筑物内读取的已经过精确标定的RFID标签信息回传到远程服务器进行计算处理,可实现建筑物外指挥员对室内消防员的实时精准定位和指挥功能.     

基于改进粒子滤波的RFID室内目标定位算法

针对于LANDMARC算法的RFID室内定位精度受传输路径影响严重,直接采用粒子滤波自适应性差的问题,提出一种基于改进粒子滤波的RFID室内定位算法.该算法首先利用极限学习机(ELM)拟合阅读器接收信号强度与标签距离之间的非线性关系,构建信号传输模型,筛选邻近标签集;然后采用自适应学习因子优化粒子滤波过程,提高粒子全局...     

基于物联网的RFID室内定位系统设计

本文研究并提供一款室内环境下进行定位的STM32定位系统,以解决卫星信号到达地面时较弱、不能穿透建筑物的问题.系统使用RFID射频识别技术实现室内定位,具有可靠性高、稳定性好、可24小时不间断工作、成本相对低等优势.使用该技术可以提高室内定位服务的信息化水平、自动化水平、减轻相关企业的生产成本,实现企业安全管理、减少人力资源的使用、降低人力成本,提高工作服务效率.     

Wear-free indoor fall detection based on RFID and deep residual networks

Since falls of the elderly can easily cause serious health problems in daily life, fall detection has received the attention of researchers. Traditionally, wearable sensors have been used to detect whether a person has fallen. However, wearable sensors may bring inconvenience to users' activities and affect user experience. In this paper, a fall detection approach based on RFID is proposed. In the proposed approach, non-contact passive tags are used to construct an array of tags. Fall detection will be performed without the user wearing the device. The RSSI and phase data are collected when the reader queries the tags. Furthermore, an action segmentation algorithm is designed to quickly extract human action information based on the short-term variance change of the phase signal. Subsequently, a deep residual network is built to classify fall movements and daily movements. Experiments show that the system can handle differences among users and locations and has an excellent performance in terms of recognition accuracy and efficiency, with an average accuracy rate of 96.77%.     

一种支持无线局域网IP移动性的体系

本文首先介绍了在WLAN中引入基于代理服务器体系的动机,然后重点介绍了该体系支持IP移动性的工作机制,最后给出了结论。     

Using enhanced-TDOA measurement for indoor positioning

In the field of ad hoc networks, maintaining connectivity and performing efficient energy communication between several mobile stations (MS), involves the use of optimized geo localization based routing algorithms. With multipath contribution, indoor location based on a direct time difference of arrival (TDOA) measurement can dramatically increase its budget error and asks for innovative solutions allowing accurate time-of-flight measurement. A natural way of exploiting multiband ultrawide-band (UWB) technology, a simple input and multiple output (SIMO) approach can lead to the measurement of an enhanced TDOA (E-TDOA) measurement for accurate positioning.     

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.     

Broadband ultrasonic location systems for improved indoor positioning

Ultrasonic location systems are a popular solution for the provision of fine-grained indoor positioning data. Applications include enhanced routing for wireless networks, computer-aided navigation, and location-sensitive device behavior. However, current ultrasonic location systems suffer from limitations due to their use of narrowband transducers, This paper investigates the use of broadband ultrasound for indoor positioning systems. Broadband ultrasonic transmitter and receiver units have been developed and characterized. The utilization of these units to construct two positioning systems with different architectures serves to highlight and affirm the concrete, practical benefits of broadband ultrasound for locating people and devices indoors.     

An indoor radio propagation model considering angles for WLAN infrastructures

Wireless local area network fingerprint‐based indoor location system is a hot topic these years because it needs no extra hardware and is very easy to deploy. However, it demands a database containing the distribution of received signal strength (RSS) of the area of interest,called radio map. Conventionally, we need to grid the area densely and manually measure RSS values on intersections, which will consume a lot of time and human resources. What is worse, change of the environment may render this database totally useless. Our consideration is to measure RSS on a small amount of these intersections and use them to build a radio propagation model. Then, this model can be deployed to predict RSS values of other intersections and reconstruct the radio map. In other words, we only need to collect a very small part the radio map and utilize the radio propagation model to recover the whole one. So far, many models have been proposed, among which the one suggested by Seidel, named floor attenuation factor propagation model, achieves great balance between computational request and accuracy. But it is not compatible with environments in some scenarios. So as to compensate for this deficiency, we take into account the angles formed by signal and surfaces of obstacles, and the results show better compatibility. The proposed model has four parameters that are related to the environments, and our second contribution in this paper is to propose a method to determine them. In fact, after collecting a small part of the radio map, we can estimate these parameters with least square method. Then, these parameters can be used to predict the signal strength at any other points in the same environment, and the whole radio map is rebuilt. According to practical experiments, performance of the radio map built by the proposed model is not as good as the manually collected one, but 80% of collecting labor is saved. Copyright © 2015 John Wiley & Sons, Ltd.     

浅析室内定位技术及应用

本文阐述了几种室内定位方法,介绍了几种主流室内定位技术,并对室内定位的应用进行了深刻分析.     

Gateway performance for network‐controlled WLAN IP mobility

‘Always on’ broadband‐accessed network gateway (GW) control can facilitate inter‐WLAN IP mobility, with seamless connectivity. The GW server plays a critical role in the overall WLAN IP (WIP) mobility architecture (IEEE Wireless Communications and Networking Conference, WCNC, Atlanta, GA, 21 March 2004; Int. J. Wireless Inf. Networks 2006; 13 (3):173–192). This paper provides a comparison of WIP with cellular IP (CIP) and mobile IP (MIP), and identifies the main requirements for a broadband‐accessed network‐based GW that supports WIP mobility. The paper then evaluates GW‐contributed handoff message processing delay in the WIP architecture through an analytical system model and OPNET simulation model, and provides a comparison of the GW‐contributed handoff message processing delays for non‐preemptive vs preemptive queuing schemes. Both analytical and simulation results show that WIP handoff message processing delay at the GW has negligible impact on the overall system delay. Finally, this paper presents the simulation results of the fast routing table lookup and forwarding speed on the GW overall performance, which can assist service providers in the challenging implementation issues that they face. Copyright © 2007 John Wiley & Sons, Ltd.     

A new method for improving Wi-Fi-based indoor positioning accuracy

Wi-Fi- and smartphone-based positioning technologies are playing a more and more important role in location-based service industries due to the rapid development of the smartphone market. However, the low positioning accuracy of these technologies is still an issue for indoor positioning. To address this problem, a new method for improving the indoor positioning accuracy was developed. The new method initially used the nearest neighbour (NN) algorithm of the fingerprinting method to identify the initial position estimate of the smartphone user. Then two distance correction values in two roughly perpendicular directions were calculated by the path loss model based on the two signal strength indicator values observed. The systematic error from the path loss model were eliminated by differencing two model-derived distances from the same access point. The new method was tested and the results compared and assessed against that of the commercial Ekahau RTLS system and the NN algorithm. The preliminary results showed that the positioning accuracy has been improved consistently after the new method was applied and the root mean square accuracy improved to 3.3 m from 3.8 m compared with the NN algorithm.     

A novel layer 3 based movement detection algorithm for improving the performance of mobile IP

Mobile IP (MIP) provides efficient mobility support to applications at transport layer or above. MIP can provide better quality of service (QoS) in heterogeneous environment if it relies on layer 3 based movement detection techniques. Among the existing movement detection algorithms (MDAs), enhanced lazy cell switching (ELCS) provides better performance compared to eager cell switching (ErCS) and early cell switching (EyCS) by reducing movement detection delay when the mobile node (MN) crosses the overlapping cells. On the other hand, movement detection delay incurred by ErCS is always low compared to ELCS while the MN crosses adjacent cells. Thus, in this paper we propose a new MDA by retaining the positive features of ErCS and ELCS to provide better QoS in a network that comprises overlapping cells and adjacent cells. Our proposed MDA reduces the usage of radio resources of the MN and foreign agent (FA) in overlapping zone compared to ELCS. The simulation results on NS-2 demonstrates that our proposed MDA improves the performance of MIP as compared to other MDAs in terms of number of TCP data packets received by the MN, TCP throughput and amount of data transferred during simulation while MN crosses the overlapping area of two cells as well as when it roams in a network consisting of both types of cells overlapping and adjacent.     

基于RFID和WLAN技术的物联网应用分析

物联网把新一代IT技术充分运用在各行各业之中,射频识别（RFID）和无线局域网（WLAN）技术是物联网的重要组成部分。在描述了RFID和WLAN的技术原理和网络结构的基础上,研究了这2种技术联合应用的系统方案,分析了1个应用的实例,最后对其市场前景进行展望。分析表明,RFID和WLAN的联合应用,充分发挥了WLAN和RFID的特点,能够为用户提供更快捷、更灵活的识别服务,具有广阔的市场前景。     

A novel UWB channel identification parameter for indoor positioning applications

We propose a new channel identification parameter that is based on the number of significant paths within the received signal. Our proposed parameter can achieve similar or better results compared to other existing methods with lower complexity. Moreover, our results show that it is possible to use only two channel identification parameters instead of three in joint channel identification techniques, as it was used in conventional methods.