Sensor data fusion for an indoor and outdoor localization

被引:3
|
作者
Belakbir A. [1 ]
Amghar M. [1 ]
Sbiti N. [1 ]
机构
[1] Mohammed V-Agdal University, Rabat
关键词
Indoor positioning systems - Sensor data fusion;
D O I
10.3103/S0735272714040013
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Geolocation systems are constantly evolving to enhance the integrity, accuracy and availability. Today, the applications are emerging and multiplying which are parts of an overall context of mobility. In outdoor environments, GNSS systems used, such as GPS and Galileo, provide a good accuracy, but in the indoor environments, GNSS signal is deteriorated due to the signal degradation by different obstacles. Many techniques are used to locate users in the indoor environments such as Infrared, Ultrasound or Radiofrequency techniques. The use of these techniques facilitates the exchange and dissemination of information. This paper presents a new design of Indoor-Outdoor positioning system based on the combination of data from UWB and GPS sources. © Allerton Press, Inc., 2014.
引用
收藏
页码:149 / 158
页数:9
相关论文
共 50 条
  • [1] Robot Localization in Indoor and Outdoor Environments by Multi-sensor Fusion
    Yousuf, Sofia
    Kadri, Muhammad Bilal
    [J]. 2018 14TH INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES (ICET), 2018,
  • [2] Indoor Blind Localization of Smartphones by Means of Sensor Data Fusion
    Ayllon, David
    Sanchez-Hevia, Hector A.
    Gil-Pita, Roberto
    Utrilla Manso, Manuel
    Rosa Zurera, Manuel
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2016, 65 (04) : 783 - 794
  • [3] INDOOR BLIND LOCALIZATION OF SMARTPHONES BY MEANS OF SENSOR DATA FUSION
    Ayllon, David
    Sanchez-Hevia, Hector
    Gil-Pita, Roberto
    Rosa-Zurera, Manuel
    [J]. 2015 IEEE SENSORS APPLICATIONS SYMPOSIUM (SAS), 2015, : 458 - 463
  • [5] Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots
    Marin, Leonardo
    Valles, Marina
    Soriano, Angel
    Valera, Angel
    Albertos, Pedro
    [J]. SENSORS, 2013, 13 (10) : 14133 - 14160
  • [6] NeuralIO: Indoor-Outdoor Detection via Multimodal Sensor Data Fusion on Smartphones
    Wang, Long
    Sommer, Lennard
    Zhou, Yexu
    Huang, Yiran
    Wang, Jingsi
    Riedel, Till
    Beigl, Michael
    [J]. SENSORS AND MATERIALS, 2020, 32 (01) : 1 - 12
  • [7] Accurate Localization for Indoor and Outdoor Scenario by GPS and UWB Fusion
    Luo, Jie
    Yin, Zhengshuai
    Gui, Linqiu
    Yang, Xu
    [J]. 2023 9TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND ROBOTICS, ICCAR, 2023, : 411 - 416
  • [8] Indoor Localization with multi sensor data fusion in ad hoc mobile scenarios
    Minutolo, Riccardo
    Annoni, Luca Alfredo
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON ULTRA-WIDEBAND (ICUWB), 2014, : 403 - 408
  • [9] Flexible Indoor Localization and Tracking Based on a Wearable Platform and Sensor Data Fusion
    Colombo, Alessio
    Fontanelli, Daniele
    Macii, David
    Palopoli, Luigi
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2014, 63 (04) : 864 - 876
  • [10] Sensor Fusion for Octagon - an Indoor and Outdoor Autonomous Mobile Robot
    Tian, Kaiqiao
    Mirza, Khalid
    [J]. SYSCON 2022: THE 16TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON), 2022,