Differential Positioning with Bluetooth Low Energy (BLE) Beacons for UAS Indoor Operations: Analysis and Results

被引:1
|
作者
Ponte, Salvatore [1 ]
Ariante, Gennaro [2 ]
Greco, Alberto [2 ]
Del Core, Giuseppe [2 ]
机构
[1] Univ Campania L Vanvitelli, Dept Engn, I-81031 Aversa, Italy
[2] Univ Naples Parthenope, Dept Sci & Technol, I-80133 Naples, Italy
关键词
UAS; indoor positioning system; BLE beacon; RSSI; trilateration; extended Kalman filter; differential distance correction; CHALLENGES; ACCURACY;
D O I
10.3390/s24227170
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Localization of unmanned aircraft systems (UASs) in indoor scenarios and GNSS-denied environments is a difficult problem, particularly in dynamic scenarios where traditional on-board equipment (such as LiDAR, radar, sonar, camera) may fail. In the framework of autonomous UAS missions, precise feedback on real-time aircraft position is very important, and several technologies alternative to GNSS-based approaches for UAS positioning in indoor navigation have been recently explored. In this paper, we propose a low-cost IPS for UAVs, based on Bluetooth low energy (BLE) beacons, which exploits the RSSI (received signal strength indicator) for distance estimation and positioning. Distance information from measured RSSI values can be degraded by multipath, reflection, and fading that cause unpredictable variability of the RSSI and may lead to poor-quality measurements. To enhance the accuracy of the position estimation, this work applies a differential distance correction (DDC) technique, similar to differential GNSS (DGNSS) and real-time kinematic (RTK) positioning. The method uses differential information from a reference station positioned at known coordinates to correct the position of the rover station. A mathematical model was established to analyze the relation between the RSSI and the distance from Bluetooth devices (Eddystone BLE beacons) placed in the indoor operation field. The master reference station was a Raspberry Pi 4 model B, and the rover (unknown target) was an Arduino Nano 33 BLE microcontroller, which was mounted on-board a UAV. Position estimation was achieved by trilateration, and the extended Kalman filter (EKF) was applied, considering the nonlinear propriety of beacon signals to correct data from noise, drift, and bias errors. Experimental results and system performance analysis show the feasibility of this methodology, as well as the reduction of position uncertainty obtained by the DCC technique.
引用
收藏
页数:24
相关论文
共 50 条
  • [21] A stigmergic approach to indoor localization using Bluetooth Low Energy beacons
    Palumbo, Filippo
    Barsocchi, Paolo
    Chessa, Stefano
    Augusto, Juan Carlos
    2015 12TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE (AVSS), 2015,
  • [22] Smartphone-Based Indoor Localization with Bluetooth Low Energy Beacons
    Zhuang, Yuan
    Yang, Jun
    Li, You
    Qi, Longning
    El-Sheimy, Naser
    SENSORS, 2016, 16 (05)
  • [23] RSSI Based Bluetooth Low Energy Indoor Positioning
    Mussina, Aigerim
    Aubakirov, Sanzhar
    2018 IEEE 12TH INTERNATIONAL CONFERENCE ON APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES (AICT), 2018, : 301 - 304
  • [24] Indoor Positioning System using Bluetooth Low Energy
    Kalbandhe, Ankush A.
    Patil, Shailaja. C.
    2016 INTERNATIONAL CONFERENCE ON COMPUTING, ANALYTICS AND SECURITY TRENDS (CAST), 2016, : 451 - 455
  • [25] RSSI Based Bluetooth Low Energy Indoor Positioning
    Zhu Jianyong
    Chen Zili
    Luo Haiyong
    Li Zhaohui
    2014 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 2014, : 526 - 533
  • [26] Towards an Indoor Navigation System using Bluetooth Low Energy Beacons
    Campana, Fernando
    Pinargote, Adriano
    Dominguez, Federico
    Pelaez, Enrique
    2017 IEEE SECOND ECUADOR TECHNICAL CHAPTERS MEETING (ETCM), 2017,
  • [27] Implementation of Android Application for Indoor Positioning System with Estimote BLE Beacons
    Song, Wook
    Lee, HwaMin
    Lee, Seung-Hyun
    Choi, Min-Hyung
    Hong, Min
    JOURNAL OF INTERNET TECHNOLOGY, 2018, 19 (03): : 871 - 878
  • [28] Indoor Positioning using BLE Beacons and User Equipments in Factory Environment
    Yuzawa, Kohei
    Fujii, Takeo
    2024 FIFTEENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS, ICUFN 2024, 2024, : 28 - 33
  • [29] Analysis of Distance and Similarity Metrics in Indoor Positioning Based on Bluetooth Low Energy
    de Blasio, Gabriel
    Quesada-Arencibia, Alexis
    Garcia, Carmelo R.
    Moreno-Diaz Jr, Roberto
    Carlos Rodriguez-Rodriguez, Jose
    UBIQUITOUS COMPUTING AND AMBIENT INTELLIGENCE, UCAMI 2017, 2017, 10586 : 213 - 224
  • [30] Enhancing Indoor Localisation: a Bluetooth Low Energy (BLE) Beacon Placement approach
    Dias, Joao
    Oliper, Duarte
    Soares, Miguel Roque
    Viana, Paula
    2024 IEEE 22ND MEDITERRANEAN ELECTROTECHNICAL CONFERENCE, MELECON 2024, 2024, : 550 - 555