Indoor Positioning and Tracking by Coupling IMU and UWB with the Extended Kalman Filter

被引:11
|
作者
Krishnaveni, B. Venkata [1 ]
Reddy, K. Suresh [2 ]
Reddy, P. Ramana [1 ]
机构
[1] Jawaharlal Nehru Technol Univ Anantapur, Elect & Commun Engn Dept, Ananthapuramu, India
[2] G Pulla Reddy Engn Coll Autonomous, Elect & Commun Engn Dept, Kurnool, India
关键词
Detection-by-tracking; Extended Kalman filter 2D; 3D tracking; Indoor positioning; IOT; UWB; LOCALIZATION;
D O I
10.1080/03772063.2022.2028580
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The goal of making each related object "location aware," or "answering the where," could boost the value of Internet of Things applications (IoT). Ultra-wideband (UWB) is applied in many services. UWB is used as the Real-Time Location System (RTLS), empowering the influence of things to come. Its reception in consumer smartphones and industrial indoor frameworks has made the RF technology watch regardless of the industry. It evident that understanding UWB is indispensable to planning future-evidence target tracking and indoor positioning systems with high accuracy that carries indoor insight into the most confounded assembled conditions. The target's location is estimated by using the Iterative method, which uses time of arrival (TOA) values. The Mean Square Error is calculated and compared between 2D and 3D environments. This paper also reports the design of an object tracker that uses Inertial Measurement Unit (IMU) and Extended Kalman Filter (EKF). The performance of the EKF is displayed using simulated target tracking in a 3D environment.
引用
收藏
页码:6757 / 6766
页数:10
相关论文
共 50 条
  • [21] An Adaptive UWB/MEMS-IMU Complementary Kalman Filter for Indoor Location in NLOS Environment
    Liu, Fei
    Li, Xin
    Wang, Jian
    Zhang, Jixian
    REMOTE SENSING, 2019, 11 (22)
  • [22] Indoor Visible Light Positioning and Tracking Method Using Kalman Filter
    Wang, Xudong
    Dong, Wenjie
    Wu, Nan
    COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS, CSPS 2018, VOL II: SIGNAL PROCESSING, 2020, 516 : 1184 - 1192
  • [23] IMU/UWB sensor fusion using moving average filter for indoor positioning of mobile robot
    Lim J.-H.
    Shim J.-H.
    Jung H.
    Journal of Institute of Control, Robotics and Systems, 2020, 26 (04) : 242 - 248
  • [24] Indoor Positioning System using UWB and Kalman filter to increase the accuracy of the Localization System
    Nguyen Hoang Hai Pham
    Minh Anh Nguyen
    Sun, Chi-Chia
    2022 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN, IEEE ICCE-TW 2022, 2022, : 339 - 340
  • [25] Positioning and Tracking Using Reconfigurable Intelligent Surfaces and Extended Kalman Filter
    Ammous, Mustafa
    Valaee, Shahrokh
    2022 IEEE 95TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-SPRING), 2022,
  • [26] Integrated iBeacon/PDR Indoor Positioning System Using Extended Kalman Filter
    Zhang, Hengrui
    Duan, Qichang
    Duan, Pan
    Hu, Bei
    PROCEEDINGS OF THE ADVANCES IN MATERIALS, MACHINERY, ELECTRICAL ENGINEERING (AMMEE 2017), 2017, 114 : 9 - 16
  • [27] Improved Height Estimation Using Extended Kalman Filter on UWB-Barometer 3D Indoor Positioning System
    Li J.
    Wang Y.
    Chen Z.
    Ma L.
    Yan S.
    Wireless Communications and Mobile Computing, 2021, 2021
  • [28] Indoor robot navigation by coupling IMU, UWB, and encode
    Ma, Siyuan
    Zhang, Yong
    Xu, Yuan
    Wang, Bin
    Cheng, Jin
    Zhao, Qinjun
    PROCEEDINGS OF 2016 10TH INTERNATIONAL CONFERENCE ON SOFTWARE, KNOWLEDGE, INFORMATION MANAGEMENT & APPLICATIONS (SKIMA), 2016, : 429 - 432
  • [29] Hybrid TDOA/AOA Indoor Positioning and Tracking Using Extended Kalman Filters
    Wann, Chin-Der
    Yeh, Yi-Jing
    Hsueh, Chih-Sheng
    2006 IEEE 63RD VEHICULAR TECHNOLOGY CONFERENCE, VOLS 1-6, 2006, : 1058 - 1062
  • [30] An Integrated IMU and UWB Sensor Based Indoor Positioning System
    Yao, Leehter
    Wu, Yeong-Wei Andy
    Yao, Lei
    Liao, Zhe Zheng
    2017 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 2017,