Indoor localization for pedestrians with real-time capability using multi-sensor smartphones

ABSTRACT

The localization of persons or objects usually refers to a position determined in a spatial reference system. Outdoors, this is usually accomplished with Global Navigation Satellite Systems (GNSS). However, the automatic positioning of people in GNSS-free environments, especially inside of buildings (indoors) poses a huge challenge. Indoors, satellite signals are attenuated, shielded or reflected by building components (e.g. walls or ceilings). For selected applications, the automatic indoor positioning is possible based on different technologies (e.g. WiFi, RFID, or UWB). However, a standard solution is still not available. Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions, e.g. additional infrastructures or sensor technologies. Smartphones, as popular cost-effective multi-sensor systems, is a promising indoor localization platform for the mass-market and is increasingly coming into focus. Today’s devices are equipped with a variety of sensors that can be used for indoor positioning. In this contribution, an approach to smartphone-based pedestrian indoor localization is presented. The novelty of this approach refers to a holistic, real-time pedestrian localization inside of buildings based on multi-sensor smartphones and easy-to-install local positioning systems. For this purpose, the barometric altitude is estimated in order to derive the floor on which the user is located. The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors. In order to minimize the strong error accumulation in the localization caused by various sensor errors, additional information is integrated into the position estimation. The building model is used to identify permissible (e.g. rooms, passageways) and impermissible (e.g. walls) building areas for the pedestrian. Several technologies contributing to higher precision and robustness are also included. For the fusion of different linear and non-linear data, an advanced algorithm based on the Sequential Monte Carlo method is presented.     

GNSS接收机DCB短期时变特征分析和估计方法

提出一种使用非差非组合精密单点定位(PPP)估计和分析接收机DCB短时时变特征的方法。首先利用非差非组合PPP得到包含接收机DCB的重构电离层参数估值;然后通过IGS电离层GIMs格网模型内插剥离各历元站星斜向电离层距离延迟;最后通过最小二乘约束得到各历元接收机DCB解。由于格网本身精度(2~8 TECU)和插值精度限制,解算出来的接收机DCB并不能真实反映其短期时变特征。为此,提出利用站间单差或者历元间差分的方法还原其真实的变化态势。实验结果表明,所提出的方法能够正确估计接收机DCB,并能真实还原其短期时变特征,具有良好的适用性。     

RTK无验潮水深测量误差分析及控制方法

实时动态(real time kinematic,RTK)无验潮水深测量技术已成为海洋测绘发展的方向。从RTK无验潮水深测量原理和误差来源入手,定性与定量分析了高程拟合误差、波浪引起的误差、仪器测量误差、定位时延以及仪器安装等误差对成果精度的影响,指出选择恰当的拟合模型是控制高程拟合误差的关键,安装姿态传感器可以削弱波浪引起的误差,提出测量前对换能器连接杆进行垂直度测量、采用双频接收机和PPS等控制方法可以有效减小测量误差。结合实践提出减小RTK无验潮水深测量精度四点建议,为RTK无验潮水深测量技术的推广应用提供参考。     

斜向和多向不规则波在斜坡堤上的平均越浪量的试验研究

通过三维物理模型试验研究了在斜坡堤上斜向和多向不规则波在非破碎条件下的平均越浪量与波浪参数及堤参数的关系.着重考察了波浪以小角度(0°~30°)斜向入射时平均越浪量的变化情况,肯定了多向波的越浪量在这一范围内有所谓“小角度斜向增加”的现象,但否定了单向波也具有这一现象.在考察波浪的方向分布影响时发现波浪斜向入射时多向波的越浪量往往要比单向波的大.比较了已有的相关研究成果,给出了适用于混凝土护面和扭工字块体护面斜坡堤上斜向和多向不规则波的平均越浪量的估算公式.     

卫星导航系统定位精度评估

对用户等效距离误差结合精度衰减因子（DOP）值的精度评估方法进行了阐述,提出根据单站DOP和全球DOP进行系统定位精度评估的两种方法,仿真证明,两种方法评估结果相当。     

三维激光扫描单点定位精度评定方法研究

三维激光扫描技术是当前的一种新技术,其仪器的精度评定方法还不完善,提出两种三维激光扫描单点定位精度评价方法,即外部符合精度评价方法和内部符合精度评价方法。介绍了两种方案的实施过程,并且通过实验进行了分析,得到了较好的评价结果。     

面向流媒体传输的空间数据变化累积模型

将流媒体技术引入到以矢量数据为主的网络GIS传输中,其关键是建立逐级精细化的多层次表达模型,并在服务器端数据预组织上建立线性索引结构。本研究针对该目标建立一种矢量数据多重表达的新模型,即变化累积模型,认为尺度空间中从粗到细的数据表达过程是一些"变化"的累积,"变化"表现为两个连续尺度表达间的差别,通过"变化"元素的逐渐增加或减少来实现渐进传输。基于该模型对面状数据渐进式传输进行研究,将多边形分级剖分为一系列凸壳或外接矩形的基础上建立变化累积模型,通过剖分元素的组合完成渐进式流媒体传输。     

VRS RTK在地籍测量中的应用与研究

为了解决地籍测量外业要求时间短、精度较高等技术问题,在理论研究的基础上,在某市城区采用了VRS RTK技术建立测量控制网.通过成果分析得知.由于基于载波相位的GPS相对定位具有较高精度,只要控制网变形可以忽略或者进行建模,则不需要进行相邻控制点的联测,因此布设VRS RTK是非常适合的,减少了传统控制网埋石造标工作量.在RTK多测站解算中,建立了由电离层、对流层和卫星轨道引起的GPS观测误差在空间和时间的相关模型,得出在人口密集或重要经济地区布设局域GPS网的设计与测量模式.     

The effect of current and wave on whitecap coverage via relative speed： the Atlantic Ocean case

Whitecapping plays an important role in many air-sea exchange and upper ocean processes. Traditionally, whitecap coverage is parameterized as a function of wind speed only. At present, the relative speed of ocean current to wind is considered to be important in the air-sea exchange parameterization which is the function of wind speed only. In this paper, the effects of ocean surface velocity (current velocity and wave induced velocity) and the wave parameters on whitecap coverage through relative speeds are investigated, by applying a 2-parameter whitecap coverage model to the Atlantic Ocean. It is found that the impacts of both current and wave on whitecap coverage are considerable in the most part of the Atlantic Ocean. It is interesting that the effect of wave is more significant than that of current.     

����ԳƷ��ڵ��㶨λ�е�Ӧ��

???GPSα????λ????????????????????μ?????????????λ??????????????ù????????????????????????????????棨???棩?????????????????????????????????α?????????????????????α???????????????????????λ??????????·??????????????????λ???????????????????????????????ν????????????????????????Ч????????λ?????????????????