ILONA: indoor localization and navigation system

Indoor positioning is a hot topic these days and there is a growing need for it in public buildings such as airports, hospitals, universities or shopping malls. Indoor positioning systems should be accurate, easily available for the users, with low installation and maintenance cost, which makes development challenging. Existing systems are based on various technologies such as ultrasonic, RFID, WiFi or light encoding. Moreover, these systems are tailored to a given environment and usually rely on a single technology. This paper presents the indoor localization and navigation (ILONA) System, a flexible hybrid indoor positioning and navigation framework. The ILONA System was not designed to be a solution for a single indoor positioning task but to be a standard core component of various systems. The ILONA System provides easily available positioning and navigation services for the end users. The system can manage data from the most commonly available sensors of modern smart phones. Thus, the ILONA System can perform positioning based on various technologies. ILONA System can be established at low cost because it only requires a connection between the server and the clients and WLAN is usually available. Hence, the presented ILONA System provides a widely available, hybrid indoor positioning framework at low cost to the developers of other indoor positioning solutions.     

A novel dynamic localisation system for indoor and outdoor tracking

ABSTRACT

Hybrid indoor and outdoor localisation system has generated substantial interest from researchers due to its potential use in many fields. Many research papers on hybrid localisation were focused on localisation accuracy and computation time instead of the process for seamless switching during the subject’s indoor-outdoor movement. Seamless and stable switching can improve the usability and practicality of a system in an ever-changing scenario. This paper presents a hybrid localisation system that can adapt to the changes in the environment. Two hybrid systems – Enhanced Fusion Hybrid (EFH) and Enhanced Unified Hybrid (EUH), and novel signal selection and switching algorithms suitable for dynamic environment where signal fluctuations and transient condition frequently occur, i.e. the Clean Radio Signal Label (CRSL) classification algorithm and the Adaptive Signal Thresholding (AST) algorithm are proposed. From the experimental results of EFH and EUH methods, the GPS and Wi-Fi combination produces the best results as compared to the combinations of GPS and GSM or GSM and Wi-Fi. The accuracy of estimates was improved to 2.0 m to 5.0 m. Further work shown that an accuracy of 2.0 m or less could be achieved with an increase in Wi-Fi nodes from three to four for the system.     

一种室内无线网络多用户自适应定位及跟踪算法

室内移动网络中各用户的路由策略和其所在的位置紧密相关,所以为提供高效的路由方案,首先要实现准确的室内定位。同时,某些特定的部门,如警方、军方和消防等,更加迫切的需要实用的室内定位算法。但是由于室内环境复杂性的影响,手机和各接收机的距离估计可能存在严重误差。针对复杂的室内环境,提出了一种利用测量到用户之间的接收功率实现定位及跟踪的算法。仿真和模拟证明该方法是有效的。     

Implementation of a real-time passive ultrasonic angle estimator for autonomous low power ranging and tracking systems

Indoor localisation technologies have received considerable attention in recent years and they are applicable in many fields. As with outdoor systems, they both suffer degradation in performance when multi-path errors are present. Applications include locating essential equipment in hospitals and specific items in warehouses, tracking people with special needs, who are away from visual supervision, and navigating firefighters inside buildings. In this article, we study issues associated with the implementation of a passive low cost, low computational complexity and low power consumption ranging and tracking system using ultrasonic sensor arrays. Due to the physical limitation of these sensors, they are placed in a zig-zag configuration to simulate an approximate linear array. To perform localisation, this system utilises the matrix pencil algorithm to estimate the direction-of-arrival (DOA) of the signal based on the phase delays of the array elements whereas the range estimation is performed by triangulation, based on DOA information from two identical arrays. Multi-access capability is also implemented to accommodate a multiple-transmitter environment. We present real-time experimental results to illustrate the satisfactory performance of the ranging and tracking system in an indoor environment setup.     

一种新型的INS与UWB融合的室内行人跟踪方法

针对单一室内定位系统定位精度低、鲁棒性差的问题,提出了一种新型的基于动态鲁棒容积卡尔曼滤波的超宽带(Ultra-wideband,UWB)与惯性导航系统(Inertial Navigation System,INS)融合的定位方法.首先建立了一种易于实现的UWB-INS融合定位框架,然后提出了一种动态鲁棒容积卡尔曼滤波...     

A pedestrian navigation system using a map-based angular motion model for indoor and outdoor environments

By incorporating known floor-plans in sequential Bayesian positioning estimators, such as particle filters, long-term positioning accuracy can be achieved as long as the map is sufficiently accurate and the environment sufficiently constrains pedestrians’ motion. Instead of using binary decisions to eliminate particles when crossing a wall, map-based angular probability density functions (PDFs) are used in this article that are capable of weighting the possible headings of the pedestrian according to local infrastructure. In addition, we will include outdoor maps by processing satellite images of the region. We will show that the angular PDFs will help to obtain better performance in critical multi-modal navigation scenarios and in the outdoor area when including maps.     

基于ROS的激光SLAM室内建图定位导航智能机器人设计

文章基于Linux系统上的ROS平台实现基本的SLAM算法,机器人可以实现构建室内地图、室内自动避障导航及室内定位等功能。底层主要以STM32和树莓派为核心,通过陀螺仪和码盘电机得到机器人方位和行走里程,使用激光雷达获取室内地图信息。在ROS上执行相应脚本,调用Gmapping,ACML算法实现室内地图构建和定位。     

基于参数拟合的室内多用户定位算法

为了提高室内环境下对目标的定位精度,提出一种室内单站精确定位技术. 该技术利用室内电波传播多径效应构成的复杂信道信息,基于机器学习,构建卷积神经网络架构,通过卷积提取不同位置目标到达接收传感器的多径时延特征信息;然后通过多层全连接层深度神经网络的模型训练,将基于复杂信道的定位问题转化为回归模型的问题,建立信道指纹与位置之间的非线性关系来完成被动定位. 训练和仿真结果表明,在室内复杂电波传播环境下,基于神经网络的室内单站精确定位技术能够实现单接收站情况下对目标的精确定位. 本文主要对3×3网格大小的金属散射体进行定位,接收站位于室内时,平均定位误差为0.621个网格（12.42 cm）;接收站位于室外时,能够分别实现信噪比20 dB、30 dB、40 dB情况下44.09 cm、21.42 cm、20.96 cm的平均定位误差. 本文方法为室内复杂环境下的目标定位提供了一种新的定位方法.     

机动测控单元定姿定位及目标捕获技术

为满足动中测控的机动测控设备建设需求,根据天线姿态误差对角精度误差的影响分析,提出了运动中天线姿态误差的定量计算方法,采用一种合理的天线稳定和目标捕获方法,对运动中目标捕获跟踪的影响因素进行了定量分析。通过机动测控单元样机对在轨卫星试验动态跟踪的数据研究,验证了姿态误差计算方法的可行性,为动中测控建设提供了有效的技术途径。