浅谈基于GPS与AGPS的双重定位

由于当前世界LBS（基于位置服务）的长足发展和Android手机用户的日益增加,为使手机的定位功能更加全面,LBS作为手机用户的一项增值业务,需要把GPS（全球卫星定位系统）技术和AGPS（辅助全球卫星定位系统）技术有机的结合起来。该文通过分析当前GPS技术和AGPS技术的优势和不足,以及所造成的对整个定位系统的影响。在这两种技术相结合的基础上去实现一个全新的Android智能手机定位系统,在这个系统下,既保留着GPS定位系统的优势,又通过与AGPS技术的结合,解决了GPS技术的缺陷。该文提出的GPS技术和AGPS技术相结合对整个定位系统都有很好的参考价值。     

An integrated approach to facility location problems

An integrated analysis approach to facility location problems is described. The approach is based on integrating analytical location models and a multicriteria decision model.     

基于室内外定位的校园LBS研究

提出基于室内外定位的校园LBS平台总体框架,设计中心平台、移动终端和信息亭结构。给出室内定位系统,研究基于ZigBee的室内无线定位网络的部署原则和方法,建立基于室内外定位的校园LBS平台原型演示验证系统,该系统实现了终端定位、地图查询、三维浏览、导航与导游、跟踪监控、短信通知等功能。     

基于动态K值及AP MAC地址筛选的室内定位算法

在简单介绍动态K值加权室内定位算法(EWKNN)并分析其不足的基础上,探索研究了基于动态K值及AP MAC地址筛选的室内定位算法。该算法首先使用EWKNN方法动态选择参考点个数,并根据测试点和参考点之间AP的MAC匹配度,进一步筛选出最优的定位参考点;最后采用得到的最优参考点与测试点之间的距离进行加权定位。实验表明,相对于传统的EWKNN定位算法,提出的算法具有较高的定位精度。     

基于Dempster-Shafer的飞行机器人多目标视觉定位方法

在受到遮挡物影响的室内环境中,飞行机器人接收数据中常伴有不确定性因素,为了解决复杂室内环境下高精准定位问题,提出了基于Dempster-Shafer的飞行机器人多目标视觉定位方法。根据飞行机器人控制原理,分析飞行位置与期望位置存在偏差,通过提取颜色特征和边缘特征建立多目标模型。设计地面标记,采用迭代算法对标记地面目标进行局部最大化概率计算,以此适应多目标形变,通过Dempster-Shafer证据推理方法获取目标精准位置,由此完成多目标视觉定位。在实验场地支持下,将传统方法与Dempster-Shafer证据推理方法进行对比分析,由结果可知,Dempster-Shafer证据推理方法定位精准度最高可达到96%,对提高室内定位精准度具有一定价值。     

Sensor Web支持下的租赁车辆远程监控系统设计与实现

对于大型的租赁公司来说,租赁车辆类型多种多样,不同车型安装的定位设备多来自于不同的生产商,这些设备在数据传输协议和数据存储格式上存在很大差异,导致资源难以互通互联。现有的关于租赁车辆远程监控方案只是针对单一定位设备进行数据管理,难以实现多源定位设备获取数据的融合。为解决以上问题,开展多源定位设备接入管理研究,构建一个兼容多源定位设备的租赁车辆远程监控系统。通过对GT220和GT710这两种来自不同厂商的定位设备建模注册,利用Sensor Web标准中的传感器观测服务（SOS,Sensor Observation Service）对多源定位设备及其观测信息进行统一管理;基于Java、AJAX、MINA框架等技术研发了租赁车辆远程监控系统;基于HTML、CSS、JavaScript等技术开发了简洁友好的前端监控页面,实现了车辆实时位置查询、历史轨迹回放、电子围栏报警等功能。对GT220和GT710两种定位设备的仿真实验表明,该系统能准确获取租赁车辆的定位信息,并实现实时跟踪、越界报警。     

Fingerprinting based localization in heterogeneous wireless networks

Due to advances in mobile technology, context-aware applications are continuously growing in importance; therefore, the ability of developing accurate and reliable localization system has become a necessity. Since methods based on received signal strength (RSS) fingerprints are today widely adopted and most of mobile devices comprise different wireless access technologies, it is feasible to use fingerprints from heterogeneous wireless networks (HWN) for localization purposes. In this paper we propose a novel approach for localization based on searching the area which best matches the test RSS fingerprint. We evaluated the proposed method in realistic environment in WLAN, GSM and UMTS networks, and compared it with other commonly used approaches. The results showed that our method compares favorably to others, and practically always achieves the lowest localization error. We also extended the proposed system using a model of cooperative positioning by combining the estimates obtained in the heterogeneous wireless network. The obtained results showed that with combined location estimate, significant improvement over any single system was achieved.     

基于无线局域网的三点定位模型

目前的无线局域网定位模型并不成熟,主要有基于信号强度和依赖数据库的定位模型,缺乏大量实验的验证.基于信号强度的无线局域网物理定位模型由于信号常常受到环境因数干扰,难以准确描述信号强度与距离的变化规律,影响定位的精确性.提出了三点定位模型和基于插值的定位算法,算法能适当地描述信号强度和距离的相对变化规律,由此弥补了由信号强度波动引起的偏差,并且通过调整衰减比例得到比传统算法更好的精确度,同时降低了传统算法采样的复杂性.实验验证该模型叮以满足无线定位的需求,具有较好的使用价值.     

Improving the accuracy of cell-based positioning for wireless networks

One fundamental issue for location-based services and applications is solving the location-sensing problem, i.e., determining where a given node is physically located in a network. In a previous paper, we have presented a location-sensing method, called the cell-based positioning method, and its positioning accuracy for the wireless networks with a hexagonal structure and mesh structure. Unfortunately, in real situations, a wireless network may not have a hexagonal or mesh structure. Thus, in this paper we consider networks with irregular structures and present an algorithm to determine the positioning accuracy of the cell-based method in such networks. In addition, we use the simulated annealing (SA) method to determine the locations and transmission ranges of base stations in order to achieve the best possible positioning accuracy. Simulation results show that the accuracy can be improved up to 30% by the SA method. The results are useful for deploying a wireless network for location-based applications.     

An efficient metric-based (EM-B) location management scheme for wireless cellular networks

In the current era, the wireless cellular network is gaining much attention in the network mobility for qualitative service. Towards enhancing the QoS and narrowing the dilemma of network management (location management) an efficient metric-based location management technique is introduced in this paper to capture the current location of mobile subscribers. The attributes of this technique are based on metrics calculation and location management message routing path determination. First, the current mobile switching center will calculate the shortest metric-based path between current and master (previous) location of mobile terminals (user), thereafter it performs the location management procedure through the optimal suggested path by the mobile switching center. This proposed technique will reduce the signaling cost, registration delay, call setup delay, network overheads and total location management cost. The proposed analytical model checks the scalability and effectiveness of proposed system over certain attributes and a comparison is made with the existing available techniques.     

An assembly precision analysis method based on a general part digital twin model

Assembly precision analysis is one of the fundamental technologies used for controlling the assembly quality of products. Existing assembly precision analysis methods focus on identifying the assembly deviation caused by manufacturing errors of parts. They place less emphasis on the influencing factors in the assembly process, which significantly affect the reliability of the analytical results. Additionally, the lack of assembly knowledge for part models leads to a low efficiency of the assembly simulation. To address these problems, this paper presents an assembly precision analysis method based on a general part digital twin model (PDTM). The proposed PDTM integrates multi-source heterogeneous geometric models and maps assembly information from assembly semantics to geometry elements, allowing automatic assembly positioning of parts and improving the efficiency of assembly simulation. In addition to the manufacturing errors, the assembly-positioning error and mating-surface deformation are considered to quantify the impact on the key characteristics of the assembled product. Based on the real mating status simulation for the mating surfaces, the uncertainty of assembly positioning in an actual assembly is simulated by combining the small displacement torsor (SDT) theory and the Monte Carlo method. Furthermore, the mating-surface deformation can be superposed to the result of the assembly-gap calculation, improving the reliability of the analytical results. Finally, a prototype system and a case study involving a load-sensitive multi-way valve assembly process are introduced to demonstrate the applicability of the proposed method.     

基于RSSI差分似然估计的WSN节点定位算法

为了克服接收信号强度测量误差对无线传感嚣网络(WSN)节点自身定位精度的影响.在对极大似然估计定位算法和接收信号强度指示(RSSI)模型分析的基础上,定义了个体差异差分系数、距离差分系数和距离差分定位方程,把离目标节点最近的信标节点作为参考节点对基于RSSI的测距进行差分修正,并将测距差分修正和极大似然估计相结合提出了一种测距差分修正极大似然估计定位算法.算法通过RSSI进行测距,无需增加额外硬件开销,容易实现.定位精度可达2.5 m以下,适合于处理能力和能量有限的WSN节点定位.     

Research on Application of Location Technology in 3D Virtual Environment Modeling System for Substation Switch Indicator

Substation inspection work plays a very important role in ensuring the normal production and the safe operation of a transformer substation. Use of a substation inspection robot can effectively solve the omission problems of a manual inspection. It can further improve the unmanned and automation of substation and improve security of station. A substation inspection system requires the establishment of a spatial position relation between the robot and the inspection object in the monitoring station. Key technology is the spatial location of the object being detected in the substation. The position of inspection object is unknown. This paper gives technical route of monocular vision positioning system based on switch indicator sign cooperative target. The knife switch indicator is one of the most important objects in the substation inspection. Usually the switch indicator lies in the middle or top of the substation equipment and conventional method can’t measure. This paper presents a substation label measurement method based on monocular vision. In this method, the label frame of knife switch indicator is as a cooperative target. The 3D coordinates and attitude of the label frame can be calculated in a camera coordinates system. At the same time, this paper introduces an extraction process of knife brake indicator label with multi-features under complex background. At last, we do simulation experiment for positioning technology of 3D virtual environment modeling system for substation switch indicator. Simulation results show that the method introduced in this paper can realize positioning of substation switch indicator label.     

Position computation models for high-speed train based on support vector machine approach

High-accuracy positioning is not only an essential issue for efficient running of high-speed train (HST), but also an important guarantee for the safe operation of high-speed train. Positioning error is zero when the train is passing through a balise. However, positioning error between adjacent balises is going up as the train is moving away from the previous balise. Although average speed method (ASM) is commonly used to compute the position of train in engineering, its positioning error is somewhat large by analyzing the field data. In this paper, we firstly establish a mathematical model for computing position of HST after analyzing wireless message from the train control system. Then, we propose three position computation models based on least square method (LSM), support vector machine (SVM) and least square support vector machine (LSSVM). Finally, the proposed models are trained and tested by the field data collected in Wuhan-Guangzhou high-speed railway. The results show that: (1) compared with ASM, the three models proposed are capable of reducing positioning error; (2) compared with ASM, the percentage error of LSM model is reduced by 50.2% in training and 53.9% in testing; (3) compared with LSM model, the percentage error of SVM model is further reduced by 38.8% in training and 14.3% in testing; (4) although LSSVM model performs almost the same with SVM model, LSSVM model has advantages over SVM model in terms of running time. We also put forward some online learning methods to update the parameters in the three models and better positioning accuracy is obtained. With the three position computation models we proposed, we can improve the positioning accuracy for HST and potentially reduce the number of balises to achieve the same positioning accuracy.     

定位技术在虚拟现实中的应用综述

近年来,我国虚拟现实技术随着5G技术、传感器技术以及民用图形处理器的发展而快速发展,教育、交通、商业、娱乐、工业等领域对虚拟现实的需求与日俱增。虚拟现实技术是一门崭新的综合性信息技术,其中的定位技术是决定用户沉浸感和交互感的关键技术,是虚拟现实技术的重要依托。因此,需要着重对虚拟现实技术的定位技术进行总结。首先介绍了虚拟现实和定位技术;其次详细分析对比了目前虚拟现实系统中使用的典型定位技术,介绍了这些技术的原理、相关研究成果以及它们在虚拟现实中具体的运用场景;然后介绍了目前市场上主流的虚拟现实定位设备,继而讨论了虚拟现实定位技术使用的定位算法;最后介绍了虚拟现实定位技术目前存在的问题和今后的发展方向。     

Simultaneous location of a service facility and a rapid transit line

This paper presents a location problem on the plane where a single service facility and a rapid transit line have to be simultaneously located. The rapid transit line represents an alternative transportation line which can be used by clients whenever it provides a cost-saving or time-saving service, and it is given by a segment with fixed and known length. This type of problems has not previously been considered in the Location Theory literature, as we are only aware of the existence of models that consider the location of service facilities in the presence of an already located alternative transportation system or models dealing with the location of rapid transit lines to minimize the travelling time among a set of points. To solve this problem we will develop an algorithm based on some characterizations of the objective function behavior.     

基于TOF测距的无线定位系统瞬时故障分析及处理

无线定位系统在实际应用中常因环境中的电磁干扰及无线传感器网络节点自身软硬件工作状态突变等因素的影响,出现定位不准确或定位数据遗漏等瞬时故障。针对瞬时故障导致的基于TOF测距的无线定位系统定位失效,分别从TOF测距和通信两方面提出故障解决方案。实验结果表明,该方案可以有效地控制瞬时故障导致的系统定位失效,提高了无线定位系统定位有效率和精确度。     

基于LSTM-Attention的RFID移动对象位置预测

随着射频识别(RFID)技术的不断发展,其相比全球定位系统(GPS)具有高精度、数据信息量大的优势,将其应用于智能交通以预测移动对象位置受到广泛关注。然而,由于其定位基站分布离散,并且不同基站对位置预测的影响权重不同,以及长期的历史信息会来带维数灾难等,移动对象的位置预测面临着严峻的挑战。针对这些挑战,在分析现有预测算法的不足的基础上,提出了一种长短期记忆网络(LSTM)和注意力(Attention)机制相结合的机器学习模型(LSTM-Attention)。该算法将one-hot编码后的输入向量通过神经网络进行降维处理后,利用注意力机制来发掘不同的定位基站对位置预测的权重影响,最后进行位置预测。在南京交管局提供的RFID数据集上进行的对比实验表明,与现有算法相比,所提算法在预测准确性上有明显的提升。     

室内信号强度指纹定位算法改进

由于人们对基于位置服务的需求越来越高,室内定位技术在诸多领域得到了广泛的应用,而定位算法则是室内定位研究的重点。首先介绍了最近邻和KNN两种信号强度指纹定位算法,并说明了KNN信号强度指纹算法的不足。在KNN信号强度指纹定位算法的基础上,提出了改进的基于区域划分的定位算法。在定位阶段,首先对接收信号强度进行补偿和滤波处理,以降低各种外在因素对定位精度的影响;同时对定位区域进行划分,选择主参考节点,并基于加权的最近邻匹配来选择最近的信号强度指纹;最后对定位结果进行计算并验证。仿真实验表明,改进的区域划分算法相对于传统的KNN算法,定位精度提高了22.2%,达到2.1m,证明了改进算法的可行性。