Buchumschlag

Improved Bluetooth-Based Indoor Localization for Devices Heterogeneity Using Back- Propagation Neural Network

Gespeichert in:
Veröffentlicht in:IEEE Sensors Journal vol. 24, no. 17 (2024), p. 27763
1. Verfasser: Yu, Min
Weitere Verfasser: Wan, Jilin, Liu, Yang, Sun, Chao, Zhou, Baoding
Veröffentlicht:
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Neural networks
Hardware
Regression models
Artificial neural networks
Calibration
Back propagation networks
Signal strength
Algorithms
Devices
Localization
Software
Heterogeneity
Bluetooth
Online-Zugang:Citation/Abstract
Tags: Tag hinzufügen
Keine Tags, Fügen Sie das erste Tag hinzu!
Abstract:Positioning accuracy can be compromised by the heterogeneity of software and hardware among different intelligent mobile devices. This is due to the fact that the heterogeneity of different devices leads to a significant difference in the received signal strength index of the same Bluetooth access point (AP) captured at the same acquisition point of the device. To address this issue, we propose to use the honey badger algorithm back-propagation neural network (HBA-BPNN) model for calibration. The aim of this study is to calibrate the received signal strength indicator (RSSI) received by Bluetooth sensors of distinct intelligent mobile terminal devices to solve software and hardware heterogeneity issues. Second, this article uses an indoor fingerprint localization algorithm based on an improved generalized regression neural network (GRNN) model and combines it with the calibration algorithm to build a better localization model. Finally, we verified the effectiveness of the HBA-BPNN calibration model for different test intelligent mobile terminal devices and then compared and analyzed the calibration algorithm proposed in this study with different calibration algorithms. The experimental comparative analysis results show that the positioning accuracy can reach 0.84 m by combining the proposed calibration algorithm with the positioning algorithm.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2024.3429237
Quelle:Advanced Technologies & Aerospace Database