Unsupervised Learning for Solving RSS Hardware Variance Problem in WiFi Localization

Hardware variance can significantly degrade the positional accuracy of RSS-based WiFi localization systems. Although manual adjustment can reduce positional error, this solution is not scalable as the number of new WiFi devices increases. We propose an unsupervised learning method to automatically solve the hardware variance problem in WiFi localization. This method was designed and implemented in a working WiFi positioning system and evaluated using different WiFi devices with diverse RSS signal patterns. Experimental results demonstrate that the proposed learning method improves positional accuracy within 100 s of learning time.     

Symbol Timing Acquisition for Collaborative OFDM WLAN-Based A-GPS

Wide deployment of the 802.11g/n protocols for implementing next generation WLAN has encouraged research on the integration of these networks and GPS as a promising approach to enhance GPS for indoor positioning. WLAN, or WiFi, using the 802.11 standards, can be employed in several different ways as a complementary positioning technology for GPS navigation and the two can be used in an integrated framework to provide a continuous and robust positioning service. This paper presents receiver-level integration of 802.11g OFDM signals and GPS for a WiFi-based assisted-GPS acquisition in a multipath NLOS environment. Although previous research has been conducted to accomplish A-GPS systems using assistance information from other wireless networks (such as cellular networks), a lack of research exists to exploit 802.11 WLAN signals in order to provide complete assistance information including frequency, approximate user position and fine time assistance. Several practical time-domain OFDM timing techniques are evaluated under multipath conditions and an algorithm for relative time estimation is developed that is sufficient to enable an effective and complete WiFi-based A-GPS service. The proposed system can be deployed in places where WiFi coverage is available and where there is no or limited access to other synchronized systems. Examples include WiFi enabled mobile devices deployed on university campuses, hospitals and shopping malls, or tablet computers being used on public WiFi networks.     

Heterogeneous Cooperative Localization for Social Networks

Location-aware techniques has become a hot research topic with great value in commercial and military applications. Cooperative localization, which utilizes multiple sensors in portable devices to estimate locations of the mobile users in the social networks, is one of the most promising solution for the indoor geo-location. Traditional cooperative localization methods are based on ranging techniques, they are highly dependent on the distance interpreted from the received signal strength (RSS) or time of arrival from anchors. However, a precise ranging procedure demands high performance hardware which would increase the cost to the current mobile platform. In this paper, we describes four ranging-free probabilistic cooperative localization algorithms: centroid scheme, nearest neighbor scheme, kernel scheme and AP density scheme to improve the accuracy for the indoor geo-location using current mobile devices. Since the GPS sensor embedded in the smart phone is able to provide accurate location information in the outdoor area, those mobile nodes can be used as calibrated anchors. The position of the indoor mobile node can be estimated by exchanging locations and RSSs from shared wireless access points information between the target node and anchor nodes. An empirical evaluation of the system is given to demonstrate the feasibility of these cooperative localization algorithms by reporting the results in a real-world environments, e.g. suburban area and city downtown. Moreover, we compared our results with the WiFi positioning system made by Skyhook Wireless to validate the accuracy of the proposed algorithms. Meanwhile, a Monte Carlo simulation is carried out to evaluate the performance of the cooperative algorithms under different scenarios. Results show that given the same scenario setting, the AP density scheme and kernel scheme outperform than other schemes.     

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.

基于WiFi的分级室内定位

在经典的K最近邻(K-Nearest Neighbors,KNN)的WiFi定位方法中,其算法复杂度随着定位区域和定位区域内的WiFi接入点(Access Point,AP)的增加而增加,无法满足实时定位的要求.为此,提出一种分级WiFi定位算法.算法分为粗定位和精定位阶段,首先通过AP的可见性利用汉明距离寻找可能的子区域,再用KNN算法在子区域内(利用信号强度欧氏距离)进行精定位.经过实测数据验证,平均单次定位时间在KNN算法下下降了约95％,在最大后验算法下下降了约96％,表明所提分级定位框架具有延迟低的优点.     

Pinpointing users with location estimation techniques and Wi‐Fi hotspot technology

Location awareness is becoming an important capability for mobile computing; however, it has not been possible until now to provide cheap pervasive positioning systems. Wide area coverage is most famously achieved by using global positioning systems (GPS). A constellation of low‐orbit satellites cover the earth's surface. Unfortunately GPS does not work indoors and has limited success in big cities because of the ‘urban canyon’ effect. PlaceLab is a research project that attempts to solve the ubiquity issues surrounding 802.11‐based location estimation. PlaceLab, like RADAR, uses a device's 802.11 interface; however, it does not require the area to be pre‐calibrated. It predicts location via the known positions of the access points detected by the device. Commonly used systems have a number of drawbacks, including cost, accuracy and the ability to work indoors. PlaceLab is a piece of open source software developed by Intel Research that can pinpoint a user within a Wi‐Fi network. We set out here to investigate whether PlaceLab can be used as a means of establishing a user's position. This type of investigation could, if successful, pave the way for the development of other location‐based applications. This report documents the efforts to answer the above question. PlaceLab was found to work, but only in ideal locations where factors such as the number of floors and the lack of available APs did not affect its use. It was concluded that these factors prevent the system from being effective as a means of establishing a user's position in most locations on campus. Copyright © 2008 John Wiley & Sons, Ltd.     

多距融合室内定位算法研究

目前WiFi在室内环境中使用频次高,用户在通过两个相邻AP时会发生AP切换,并累计产生大量WiFi访问日志。WiFi日志中包含定位所需的接收信号强度指示符,在定位系统中直接利用WiFi访问日志中的数据,将极大地简化定位部署复杂度。文中提出了一种在两个相邻AP环境下,基于WiFi日志的多距融合室内定位算法,并通过实验仿真将新算法与路径损耗模型定位方法进行对比。实验结果表明,新算法具有易部署、低成本、低复杂度等特点,当训练样本个数达到300时即可达到稳定定位效果。     

Adaptive access points deployment for Indoor bluetooth positioning accuracy enhancement

The indoor positioning system based on fingerprint receives more and more attention due to its high positioning accuracy and time efficiency. In the existing positioning approaches, much consideration is given to the positioning accuracy improvement by using the angle of signal, but the optimization of access points (APs) deployment is ignored. In this circumstance, an adaptive APs deployment approach is proposed. First of all, the criterion of reference points (RPs) effective coverage is proposed, and the number of deployed APs in target environment is obtained by using the region partition algorithm and full coverage algorithm. Secondly, the wireless signal propagation model is established for target environment, and meanwhile based on the initial APs deployment, the simulation fingerprint database is constructed for the sake of establishing the discrimination function with respect to fingerprint database. Thirdly, the greedy algorithm is applied to optimize APs deployment. Finally, the extensive experiments show that the proposed approach is capable of achieving adaptive APs deployment as well as improving positioning accuracy.     

Land-vehicle navigation using GPS

The Global Positioning System (GPS) has made navigation systems practical for a number of land-vehicle navigation applications. Today, GPS-based navigation systems can be found in motor vehicles, farming and mining equipment, and a variety of other land-based vehicles (e.g., golf carts and mobile robots). Each of these applications is discussed and the reader is introduced to some of the issues involved with each one. One particular technical aspect of navigation for land vehicles is discussed. Specifically, the research discussed in this paper presents a quantitative examination of the impact that individual navigation sensors have on the perfomance of a land-vehicle navigation system. A range of navigation sensor performance levels and their influence on vehicle positioning accuracy are examined. Results show that, for a typical navigation system, positioning error is dominated by the accuracy of the position fixes provided by the GPS receiver when GPS position fixes are available and by the rate gyro's bias drift when GPS position fixes are not available. Furthermore, results show that the accuracy of the GPS position fixes has a significant impact on the relative contributions that each dead-reckoning navigation sensor error makes. The implications of these results for navigation system design and sensor design are discussed     

一种基于单目视觉的无人机室内定位方法

目前,无人机定位技术主要依赖以GPS(Global Positioning System)为代表的全球定位系统,然而在室内等GPS信号缺失的地方进行定位则比较困难.另外,传统的室内定位技术主要采用蓝牙、WiFi、基站定位等多种方式融合成一套定位体系,但是该类方法受环境的影响比较大,而且往往需要部署多个设备.此外,这种方...     

gpsOne定位技术研究

移动通信最显著的特点就是移动,因而自然会衍生一些和位置相关的服务需求.在不远的将来,电子邮件和定位服务将成为移动通信的两大支柱增值产业. 鉴于传统GPS及基于无线网络本身的定位技术在定位精度或定位灵敏度或系统建设或终端方面存在的重大缺陷,目前,世界上较流行的移动定位技术是无线网络辅助GPS技术及混合型定位技术.由于自身技术优势,gpsOne已无可争议的成为移动定位业界的首选技术.     

基于数字变频处理的GPS/BDS双模捕获

全球定位系统(Global Positioning System,GPS)与“北斗”定位导航系统(Beidou Navigation Satellite System,BDS)的双模导航能够提高定位稳定性与精确性,但通常在前端硬件设计中需要建立双通道对GPS和BDS射频信号分别进行处理,极大地增加了硬件设计复杂度以及功率的消耗。针对双通道硬件设计的复杂性问题,提出了在Matlab环境下对GPS/BDS双频信号进行数字变频处理的方法。该方法将硬件中的变频功能在软件中实现,从而降低了硬件设计的复杂度且保证了算法与不同全球卫星导航系统(Global Navigation Satellite System,GNSS)以及前端硬件的兼容性。实验结果表明,在不同的单通道硬件设计下,利用该方法能够成功在软件中消除与L1或B1的频偏得到捕获信号,并捕获到GPS/BDS可见卫星信息。     

应用于WiFi室内定位的自适应仿射传播聚类算法

在室内覆盖的大量的WiFi信号可以用来室内定位。尽管很多WiFi室内定位技术被提出,但其定位精度仍然未达到实际应用的需求。针对这个问题,该文提出一种自适应仿射传播聚类(AAPC)算法用以提高WiFi指纹的聚类质量,从而提高定位精度。AAPC算法通过动态调整参数生成不同的聚类结果,然后采用聚类有效性指标筛选出其中最佳的。采集大量真实环境数据进行试验,试验结果表明采用AAPC算法产生的聚类结果具有更高的定位精度。     

Optimising mobile phone self-location estimates by introducing beacon characteristics to the algorithm

Positioning technologies that use global system for mobile communication (GSM) networks for location estimation (such as the privacy observant location system (POLS) and the place lab framework) lack the accuracy that other positioning technologies like the global positioning system (GPS) have. GPS receivers are most of the time capable of placing a person within 10 m of a known location. Place Lab is an open platform framework implemented in Java for client-side location sensing that can calculate a position estimate from various beacon sources, such as GSM beacons. The POLS framework is a counterpart of Place Lab for Windows Smartphone devices which provide the tools to develop location-based services quickly. There is a lack of accuracy, however, when the location estimation algorithm uses only GSM readings. Measurements that have been made with Place Lab show a median accuracy of 232 m in downtown areas. Place Lab and POLS do not need additional hardware, apart from the mobile phone itself, however, their lack of accuracy compared to GPS is significant. Due to this rather poor accuracy, the use of those frameworks is limited to applications where the accuracy is not crucial. This article presents the results of improving the accuracy of location estimation in urban areas by extending the algorithm used in the POLS and Place Lab frameworks to take into account the beacon properties, effective radiated power (ERP) and beacon height when estimating a position. The extended algorithm based on beacon properties outperforms the centroid algorithm by over 30%.     

The Use of Aerial Images and GPS for Mobile Robot Waypoint Navigation

The application of aerial and satellite imagery for mobile robot path planning and navigation has shown potential in recent years. Their uses vary from identifying terrain properties for creating traversability maps to extracting landmarks for autonomous navigation. With the freely available differential positioning system, Wide Area Augmentation System (WAAS)/European Geostationary Navigation Overlay Service (EGNOS), the use of the GPS with aerial images providing valuable contextual data demonstrates potential in waypoint-based navigation of mobile robots. However, important issues relating to the spatial accuracies of image, waypoint, and GPS-derived data, vital for obtaining accurate navigation results, are often overseen. This paper defines the causes of spatial inaccuracies in order to develop optimal waypoint navigation parameters and provides researchers with sufficient knowledge to reproduce similar results. An improvement of up to 48% in the number of waypoints reached, depending on the radius, was determined for the positional correction of the GPS. The results are shown with a simulated synchronous drive robot in Matlab's Simulink environment. The reader is presented with a method for easily creating waypoints from aerial images, yielding results to a similar level of accuracy to conventional and often tedious manual methods.      

Location determination using WiFi fingerprinting versus WiFi trilateration

Many applications in the area of location-based services and personal navigation require nowadays the location determination of a user not only in an outdoor environment but also an indoor. Typical applications of location-based services (LBS) mainly in outdoor environments are fleet management, travel aids, location identification, emergency services and vehicle navigation. LBS applications can be further extended if reliable and reasonably accurate three-dimensional positional information of a mobile device can be determined seamlessly in both indoor and outdoor environments. Current geolocation methods for LBS may be classified as GNSS-based, cellular network-based or their combinations. GNSS-based methods rely very much on the satellite visibility and the receiver-satellite geometry. This can be very problematic in dense high-rise urban environments and when transferring to an indoor environment. Especially, in cities with many high-rise buildings, the urban canyon will greatly affect the reception of the GNSS signals. Moreover, positioning in the indoor/outdoor transition areas would experience signal quality and signal reception problems, if GNSS systems alone are employed. The authors have proposed the integration of GNSS with wireless positioning techniques such as WiFi and UWB. In the case of WiFi positioning, the so-called fingerprinting method based on WiFi signal strength observations is usually employed. In this article, the underlying technology is briefly reviewed, followed by an investigation of two WiFi-positioning systems. Testing of the system is performed in two localisation test beds, one at the Vienna University of Technology and another one at the Hong Kong Polytechnic University. The first test showed that the trajectory of a moving user could be obtained with a standard deviation of about ±3–5 m. The main disadvantage of WiFi fingerprinting, however, is the required time consuming and costly signal strength system calibration in the beginning. Therefore, the authors have investigated if the measured signal strength values can be converted to the corresponding range to the access point. A new approach for this conversion is presented and analysed in typical test scenarios.     

基于Android平台的移动通讯设备的GPS定位研究

Android平台移动通讯设备的GPS定位以其优良系统性能在人们的生活中以智能手机为媒介被广泛使用,基于此如何提高Android平台的GPS导航的精确度对于现代高科技产品的发展尤为重要。通过对GPS定位卫星所得到的原始数据处理,根据GPS卫星数据之间的联系得出有效的分析数据来弥补在定位时可能产生的误差,从而降低不安全因素,提高GPS定位的精确度。     

Offloading in Software Defined Network at Edge with Information Asymmetry: A Contract Theoretical Approach

The proliferation of highly capable mobile devices such as smartphones and tablets has significantly increased the demand for wireless access. Software defined network (SDN) at edge is viewed as one promising technology to simplify the traffic offloading process for current wireless networks. In this paper, we investigate the incentive problem in SDN-at-edge of how to motivate a third party access points (APs) such as WiFi and smallcells to offload traffic for the central base stations (BSs). The APs will only admit the traffic from the BS under the precondition that their own traffic demand is satisfied. Under the information asymmetry that the APs know more about own traffic demands, the BS needs to distribute the payment in accordance with the APs’ idle capacity to maintain a compatible incentive. First, we apply a contract-theoretic approach to model and analyze the service trading between the BS and APs. Furthermore, other two incentive mechanisms: optimal discrimination contract and linear pricing contract are introduced to serve as the comparisons of the anti adverse selection contract. Finally, the simulation results show that the contract can effectively incentivize APs’ participation and offload the cellular network traffic. Furthermore, the anti adverse selection contract achieves the optimal outcome under the information asymmetry scenario.     

Technique for order performance by similarity to ideal solution for solving complex situations in multi-criteria optimization of the tracking channels of GPS baseband telecommunication receivers

Global positioning system (GPS) has undergone intensive development, starting as an advanced specialized tool to a general-purpose gadget used in our daily lives. GPS exists in new technologies, applications, and consumer products, especially in smartphones and tablets. In a GPS receiver design, power consumption and localization accuracy are critical factors that affect the outcome of a GPS receiver system. Theoretically, increasing the number of required tracking channels in a GPS baseband receiver increases the design complexity and size of this system. Thus, power consumption can significantly increase. The receiver should acquire and track numerous satellites to improve the location accuracy of a position, thereby indicating that the receiver requires a high number of tracking channels. Thus, optimizing these tracking channels to balance the conflict among performance parameters is a difficult and challenging task. This paper presents a technique for order performance by similarity to ideal solution (TOPSIS) for solving complex situations for multi-criteria optimization of the tracking channels of GPS baseband telecommunication receiver. Nine operation modes of GPS receiver were evaluated by each design parameter, such as power consumption, localization accuracy, and time with no position available for static and dynamic positioning. Then, the TOPSIS was utilized and implemented to measure and rank the overall performance of tracking channel selection. Results of this study indicate that (1) multi-objective optimization is a reliable strategy for visualizing the trade-off among the GPS design parameters and providing a dynamic power consumption planning. (2) The best aggregated performance of the GPS receiver occurs when the number of tracking channels equals five and six for static and dynamic positioning, respectively. (3) The most frequent number of available satellites is eight, whereas the other number of satellites is a rare case to acquire. However, GPS standards require that available GPS satellites are constantly 12 at any time and place.     

Energy‐efficient network selection with mobility pattern awareness in an integrated WiMAX and WiFi network

To provide wireless Internet access, WiFi networks have been deployed in many regions such as buildings and campuses. However, WiFi networks are still insufficient to support ubiquitous wireless service due to their narrow coverage. One possibility to resolve this deficiency is to integrate WiFi networks with the wide‐range WiMAX networks. Under such an integrated WiMAX and WiFi network, how to conduct energy‐efficient handovers is a critical issue. In this paper, we propose a handover scheme with geographic mobility awareness (HGMA), which considers the historical handover patterns of mobile devices. HGMA can conserve the energy of handovering devices from three aspects. First, it prevents mobile devices from triggering unnecessary handovers according to their received signal strength and moving speeds. Second, it contains a handover candidate selection method for mobile devices to intelligently select a subset of WiFi access points or WiMAX relay stations to be scanned. Therefore, mobile devices can reduce their network scanning and thus save their energy. Third, HGMA prefers mobile devices staying in their original WiMAX or WiFi networks. This can prevent mobile devices from consuming too much energy on interface switching. In addition, HGMA prefers the low‐tier WiFi network over the WiMAX network and guarantees the bandwidth requirements of handovering devices. Simulation results show that HGMA can save about 59– 80% of energy consumption of a handover operation, make mobile devices to associate with WiFi networks with 16–62% more probabilities, and increase about 20–61% of QoS satisfaction ratio to handovering devices. Copyright © 2009 John Wiley & Sons, Ltd.