Obstruction-Aware Signal-Loss-Tolerant Indoor Positioning Using Bluetooth Low Energy

Indoor positioning is getting increased attention due to the availability of larger and more sophisticated indoor environments. Wireless technologies like Bluetooth Low Energy (BLE) may provide inexpensive solutions. In this paper, we propose obstruction-aware signal-loss-tolerant indoor positioning...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-02, Vol.21 (3), p.971
Main Authors: Taşkan, Aybars Kerem, Alemdar, Hande
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Bluetooth
Bluetooth Low Energy
Discriminant analysis
Energy
Filtration
Fingerprinting
Indoor environments
indoor positioning
Infrastructure
Methods
multilateration
Museums
Obstructions
particle filter
Position measurement
Radio frequency identification
Receivers & amplifiers
Simulation
Wireless access points
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Summary:Indoor positioning is getting increased attention due to the availability of larger and more sophisticated indoor environments. Wireless technologies like Bluetooth Low Energy (BLE) may provide inexpensive solutions. In this paper, we propose obstruction-aware signal-loss-tolerant indoor positioning (OASLTIP), a cost-effective BLE-based indoor positioning algorithm. OASLTIP uses a combination of techniques together to provide optimum tracking performance by taking into account the obstructions in the environment, and also, it can handle a loss of signal. We use running average filtering to smooth the received signal data, multilateration to find the measured position of the tag, and particle filtering to track the tag for better performance. We also propose an optional receiver placement method and provide the option to use fingerprinting together with OASLTIP. Moreover, we give insights about BLE signal strengths in different conditions to help with understanding the effects of some environmental conditions on BLE signals. We performed extensive experiments for evaluation of the OASLTool we developed. Additionally, we evaluated the performance of the system both in a simulated environment and in real-world conditions. In a highly crowded and occluded office environment, our system achieved 2.29 m average error, with three receivers. When simulated in OASLTool, the same setup yielded an error of 2.58 m.
ISSN:1424-8220
1424-8220
DOI:10.3390/s21030971