基于普适计算环境的三维空间RSSI位置感知研究

文中对室内定位应用中可能的几种技术进行了分析与对比,指出了各自的缺陷与不足。通过分析指出无线传感器网络自身的特点较其他几种技术更好地适应了普适计算环境对于位置感知服务的需求。采用无线传感器节点,把基于RSSI技术的测距方法作为研究位置感知的主要途径,提出了可行的三维空间位置感知模型及其相应的误差修正方案,并进行了充分的实验验证,证明该模型可以定位出目标较为准确的位置,其中所提出的误差修正方案很好地校正了目标点的实际位置。     

基于普适计算环境的三维空间RSSI位置感知研究

文中对室内定位应用中可能的几种技术进行了分析与对比,指出了各自的缺陷与不足.通过分析指出无线传感器网络自身的特点较其他几种技术更好地适应了普适计算环境对于位置感知服务的需求.采用无线传感器节点,把基于RSSI技术的测距方法作为研究位置感知的主要途径,提出了可行的三维空间位置感知模型及其相应的误差修正方案,并进行了充分的实验验证,证明该模型可以定位出目标较为准确的位置,其中所提出的误差修正方案很好地校正了目标点的实际位置.     

普适计算环境中基于上下文的使用控制模型

使用控制模型可以解决普适计算环境中访问控制的动态授权问题,但该模型没有考虑上下文信息。为此,提出一种普适计算环境中基于上下文的使用控制模型。在使用决策因素中增加上下文信息,包括时间、位置和环境因素,采用行为时态逻辑定义模型的核心规则集。以基于普适计算的智能教室为实例进行分析,证明该模型在普适计算环境中的有效性。     

普适计算及其定位感知系统

普适计算的目的是为了使计算机更好地为人类服务，提高人们的生活质量。普适计算中的定位感知系统是普适计算研究中的核心部分之一，如何确定室内用户的动态位置信息，如何主动向用户提供各种所需的信息，这些都是其研究话题。给出了一种自行设计的普适计算室内定位感知系统的最小功能模型。     

普适计算中的定位感知系统

普适计算的目的是为了使计算机更好地为人类服务,提高人们的生活质量。普适计算中的定位感知系统是普适计算研究中的核心部分之一。如何确定室内用户的动态位置信息,如何主动向用户提供各种所需的信息,都是本文的研究话题。文章最后给出一种自行设计的普适计算室内定位感知系统的最小功能模型。     

普适计算环境下室内定位模型的研究*

在分析了普适计算环境的特点后,指出现有的定位方案不适应普适环境下的定位要求,相应地提出一种以超声测距为原理的室内定位模型。经过性能分析证明,它能够取得良好的效果,为普适计算环境下各种服务的实现提供了一个重要的前提。     

普适计算中的室内位置感知

随着计算模式从主机计算和桌面计算逐步向普适汁算过渡,上下文感知计算是普适计算的核心研究内容,而位置感知计算在上下文感知计算研究中义具有极其重要的地位。该文综述了多种重要的室内位置感知技术,并结合作者在三维位置定位方面的研究成果介绍了各种位置感知方法,最后对位置感知模型的一般情况进行了深入探讨。     

一个普适计算环境中的定位隐私保护模型*

随着普适计算技术的发展,在普适环境中的应用服务也日益增多。这些服务通常都是基于用户位置的服务,然而,用户的定位信息中往往直接或间接地包含着用户的隐私内容。针对如何在获取个性化定制服务的同时保护用户的定位隐私这一问题展开讨论,提出了一种定位信息采集和假名使用的策略,并基于该策略建立了一个普适计算环境中的定位隐私保护模型。     

普适环境室内定位系统研究

位置感知服务是普适计算的一类重要应用。在位置感知服务中,位置信息是关键的上下文之一。如何获取位置上下文,是位置感知服务中的关键点之一。基于不同的应用背景和服务,目前已经存在大量的定位系统。从室内定位的角度,研究了定位系统中的关键技术和方法,并对各种技术进行了分析比较;在分析现有普适环境下典型的室内定位系统基础上,提出了室内定位系统所面临的挑战。     

基于多维尺度分析的自适应室内群终端定位方法

室内定位是普适计算领域的热点研究问题。当前,室内定位方法主要分为基于信号传播模型的定位方法和基于无线信号指纹的定位方法。其中,基于指纹的方法由于不需要知道无线信号接入点(Access Point,AP)的位置而得到更加广泛的应用, 其需要通过离线阶段采集大量数据来构建丰富的指纹库,满足这一条件需要大量的人工标定工作。对此,文中提出了一种基于指纹空间关系的定位方法,相比于传统的指纹定位方法,该方法无需建立指纹库,只需要通过获取多终端的 Wi-Fi 信号强度,计算所有终端的不相似度并构建不相似矩阵;通过多维尺度分析(Multidimensional Scaling,MDS)算法,构建出所有终端的位置分布图,进而通过确定其中 3 个以上终端的位置来定位所有的终端。采用支持向量回归机(Support Vector Regression,SVR)计算任意终端间的距离,并将距离矩阵作为不相似矩阵。文中在商场场景下选择了约2500m²的区域进行实验,所提方法的平均定位误差约为7m。     

Hidden Issues in Deploying an Indoor Location System

Installing indoor location system prototypes yields practical lessons about how to design and deploy future ubiquitous technologies. The design of context-aware technologies has been on many research team agendas since Mark Weiser first described his ubiquitous computing vision. Determining the location of people and objects in indoor environments with a high degree of accuracy is a main technical obstacle to achieving this vision.     

Improving location awareness in indoor spaces using RFID technology

Location awareness is a key issue to improve the development of autonomous entities that are embedded into ubiquitous computing environments. GPS seems to be the best solution to develop outdoor location systems, but the performance of these systems is not good enough to locate objects or humans within indoor environments, mainly if accuracy and precision are required. In this article we propose the use of a cheap and reliable technology as RFID to develop a passive RFID-based indoor location system that is able to accurately locate autonomous entities, such as robots and people, within a defined surface. This system is applied to solve the robot tracking problem. We include the evaluation of the proposal by comparing our system technology performance with other alternatives built on different technologies (Wi-Fi, Bluetooth, IrDA, ultrasound, etc.). We have also performed a location awareness proof concept test to analyze the viability of the approach.     

室内定位技术分析

对位置信息的识别是普适计算中的一个重要研究领域,其中大多教的应用都是在室内环境下.介绍位置识别的一般技术与方法,展示目前在室内定位领域兵有代表性的研究性和商业性的定位系统,分析各种技术的长处及其局限性,提出今后的研究方向.     

Analysis of WLAN’s received signal strength indication for indoor location fingerprinting

An indoor positioning system that uses a location fingerprinting technique based on the received signal strength of a wireless local area network is an enabler for indoor location-aware computing. Data analysis of the received signal strength indication is very essential for understanding the underlying location-dependent features and patterns of location fingerprints. This knowledge can assist a system designer in accurately modeling a positioning system, improving positioning performance, and efficiently designing such a system. This study investigates extensively through measurements, the features of the received signal strength indication reported by IEEE 802.11b/g wireless network interface cards. The results of the statistical data analysis help in identifying a number of phenomena that affect the precision and accuracy of indoor positioning systems.     

Hybrid indoor and outdoor location services for new generation mobile terminals

In the last years, an increasing interest in location services characterized the market of mobile ubiquitous devices (smartphones, handhelds, etc.). Several technologies and solutions have been developed to determine the position of mobile devices in their operating space, each with its specific degree of precision and accuracy. In this scenario, the ideal location service should be able of tracking the mobile terminal in any place it moves to, both indoors and outdoors. However, while outdoor location services have already achieved a satisfactory degree of technological maturity and effectiveness, a really ubiquitous location service that works satisfactorily in both indoor and outdoor scenarios is not yet available. In order to cope with the above challenge, this work proposes a hybrid location approach designed to choose and switch among multiple positioning technologies supported by the mobile device and available in the surrounding environment, in a dynamic and transparent way during the user movement. It combines signal strength–based fingerprinting techniques for indoor positioning together with traditional GPS-based positioning for the outdoor localization and performs opportunistic technology switching according to a count-and-threshold mechanism. The resulting solution is able to leverage the different features of the wireless networks and of the global positioning technologies, in order to provide ubiquitous location services across indoor and outdoor scenarios, as well as to minimize power consumption of the mobile device.     

Location awareness through trajectory prediction

Location-aware computing is a type of ubiquitous computing that uses user’s location information as an essential parameter for providing services and application-related optimization. Location management plays an important role in location-aware computing because the provision of services requires convenient access to dynamic location and location-dependent information. Many existing location management strategies are passive since they rely on system capability to periodically record current location information. In contrast, active strategies predict user movement through trajectories and locations. Trajectory prediction provides richer location and context information and facilitates the means for adapting to future locations. In this paper, we present two models for trajectory prediction, namely probability-based model and learning-based model. We analyze these two models and conduct experiments to test their performances in location-aware systems.     

基于分层定位模型的RFID定位算法研究

识别和定位为智能停车场等服务领域提供关键信息,基于RFID的LANDMARC算法为常见的室内定位方法。文中对低成本、高精度的经典室内定位算法LANDMARC进行分析,针对其在定位过程中单纯根据信号强度的欧几里得距离选择节点进行定位计算的不足,提出基于双层定位模型的算法D-LANDMRAC。该算法主要由初步定位和精确定位两部分组成,初步定位过滤掉问题参考标签,再基于“距离-损耗冶公式利用标签之间信号强度差进行精确定位。仿真结果表明,相比LANDMARC算法,D-LANDMRAC算法定位精度有了明显的提高,并且定位误差的分布更加均衡。     

一种基于空间分割的无源RFID室内定位方法*

为了提高室内定位系统的性能,提出了一种利用无源RFID技术定位目标物体的算法。本算法使用双层对称分布的参考标签和空间连续分割的方法提高了室内定位的精度。实际测试结果表明,本算法可较好地实现目标的三维空间定位,与传统LANDMARC定位系统相比,单个平面定位精度提升了8倍,适合于室内人员、物资等定位应用。