The Sectored Antenna Array Indoor Positioning System with Neural Networks

Chih-Yung Chen; Yu-Ju Chen; Ya-Chen Weng; Shen-Whan Chen; Rey-Chue Hwang

doi:doi:10.11648/j.acis.20160402.13

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The Sectored Antenna Array Indoor Positioning System with Neural Networks

Chih-Yung Chen, Yu-Ju Chen, Ya-Chen Weng, Shen-Whan Chen, Rey-Chue Hwang

Received: 24 March 2016 Accepted: Published: 25 March 2016

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Abstract

This paper presents a sectored antenna array indoor positioning system (IPS) with neural network (NN) technique. The hexagonal positioning station is composed of six printed-circuit board Yagi-Uda antennas and Zigbee modules. The values of received signal strength (RSS) sensed by wireless sensors were used to be the information for object’s position estimation. Two NN models, including NN with back-propagation (BP) learning algorithm and probabilistic NN (PNN), were applied to perform the positioning work for a comparison. In the experiments, an 8x8 square meters indoor scene was performed and 288 points and 440 points were experimented in this area. The positioning results show that both NN models have the average error less than 0.7 meter. In other words, the proposed positioning system not only has the high positioning accuracy, but also has the potential in real application.

DOI	10.11648/j.acis.20160402.13
Published in	Automation, Control and Intelligent Systems (Volume 4, Issue 2, April 2016)
Page(s)	21-27
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Sectored Antenna, Indoor Positioning System (IPS), Neural Network (NN), Received Signal Strength (RSS)

References

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APA Style

Chih-Yung Chen, Yu-Ju Chen, Ya-Chen Weng, Shen-Whan Chen, Rey-Chue Hwang. (2016). The Sectored Antenna Array Indoor Positioning System with Neural Networks. Automation, Control and Intelligent Systems, 4(2), 21-27. https://doi.org/10.11648/j.acis.20160402.13

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ACS Style

Chih-Yung Chen; Yu-Ju Chen; Ya-Chen Weng; Shen-Whan Chen; Rey-Chue Hwang. The Sectored Antenna Array Indoor Positioning System with Neural Networks. Autom. Control Intell. Syst. 2016, 4(2), 21-27. doi: 10.11648/j.acis.20160402.13

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AMA Style

Chih-Yung Chen, Yu-Ju Chen, Ya-Chen Weng, Shen-Whan Chen, Rey-Chue Hwang. The Sectored Antenna Array Indoor Positioning System with Neural Networks. Autom Control Intell Syst. 2016;4(2):21-27. doi: 10.11648/j.acis.20160402.13

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@article{10.11648/j.acis.20160402.13,
  author = {Chih-Yung Chen and Yu-Ju Chen and Ya-Chen Weng and Shen-Whan Chen and Rey-Chue Hwang},
  title = {The Sectored Antenna Array Indoor Positioning System with Neural Networks},
  journal = {Automation, Control and Intelligent Systems},
  volume = {4},
  number = {2},
  pages = {21-27},
  doi = {10.11648/j.acis.20160402.13},
  url = {https://doi.org/10.11648/j.acis.20160402.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20160402.13},
  abstract = {This paper presents a sectored antenna array indoor positioning system (IPS) with neural network (NN) technique. The hexagonal positioning station is composed of six printed-circuit board Yagi-Uda antennas and Zigbee modules. The values of received signal strength (RSS) sensed by wireless sensors were used to be the information for object’s position estimation. Two NN models, including NN with back-propagation (BP) learning algorithm and probabilistic NN (PNN), were applied to perform the positioning work for a comparison. In the experiments, an 8x8 square meters indoor scene was performed and 288 points and 440 points were experimented in this area. The positioning results show that both NN models have the average error less than 0.7 meter. In other words, the proposed positioning system not only has the high positioning accuracy, but also has the potential in real application.},
 year = {2016}
}

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TY  - JOUR
T1  - The Sectored Antenna Array Indoor Positioning System with Neural Networks
AU  - Chih-Yung Chen
AU  - Yu-Ju Chen
AU  - Ya-Chen Weng
AU  - Shen-Whan Chen
AU  - Rey-Chue Hwang
Y1  - 2016/03/25
PY  - 2016
N1  - https://doi.org/10.11648/j.acis.20160402.13
DO  - 10.11648/j.acis.20160402.13
T2  - Automation, Control and Intelligent Systems
JF  - Automation, Control and Intelligent Systems
JO  - Automation, Control and Intelligent Systems
SP  - 21
EP  - 27
PB  - Science Publishing Group
SN  - 2328-5591
UR  - https://doi.org/10.11648/j.acis.20160402.13
AB  - This paper presents a sectored antenna array indoor positioning system (IPS) with neural network (NN) technique. The hexagonal positioning station is composed of six printed-circuit board Yagi-Uda antennas and Zigbee modules. The values of received signal strength (RSS) sensed by wireless sensors were used to be the information for object’s position estimation. Two NN models, including NN with back-propagation (BP) learning algorithm and probabilistic NN (PNN), were applied to perform the positioning work for a comparison. In the experiments, an 8x8 square meters indoor scene was performed and 288 points and 440 points were experimented in this area. The positioning results show that both NN models have the average error less than 0.7 meter. In other words, the proposed positioning system not only has the high positioning accuracy, but also has the potential in real application.
VL  - 4
IS  - 2
ER  -

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Author Information

Chih-Yung Chen

Department of Computer and Communication, Shu-Te University, Kaohsiung City, Taiwan
Yu-Ju Chen

Department of Information Management, Cheng Shiu University, Kaohsiung City, Taiwan
Ya-Chen Weng

Department of Computer and Communication, Shu-Te University, Kaohsiung City, Taiwan
Shen-Whan Chen

Department of Communication Engineering, I-Shou University, Kaohsiung City, Taiwan
Rey-Chue Hwang

Department of Electrical Engineering, I-Shou University, Kaohsiung City, Taiwan

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Plain Text BibTeX RIS

APA Style

Chih-Yung Chen, Yu-Ju Chen, Ya-Chen Weng, Shen-Whan Chen, Rey-Chue Hwang. (2016). The Sectored Antenna Array Indoor Positioning System with Neural Networks. Automation, Control and Intelligent Systems, 4(2), 21-27. https://doi.org/10.11648/j.acis.20160402.13

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ACS Style

Chih-Yung Chen; Yu-Ju Chen; Ya-Chen Weng; Shen-Whan Chen; Rey-Chue Hwang. The Sectored Antenna Array Indoor Positioning System with Neural Networks. Autom. Control Intell. Syst. 2016, 4(2), 21-27. doi: 10.11648/j.acis.20160402.13

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AMA Style

Chih-Yung Chen, Yu-Ju Chen, Ya-Chen Weng, Shen-Whan Chen, Rey-Chue Hwang. The Sectored Antenna Array Indoor Positioning System with Neural Networks. Autom Control Intell Syst. 2016;4(2):21-27. doi: 10.11648/j.acis.20160402.13

Copy | Download

@article{10.11648/j.acis.20160402.13,
  author = {Chih-Yung Chen and Yu-Ju Chen and Ya-Chen Weng and Shen-Whan Chen and Rey-Chue Hwang},
  title = {The Sectored Antenna Array Indoor Positioning System with Neural Networks},
  journal = {Automation, Control and Intelligent Systems},
  volume = {4},
  number = {2},
  pages = {21-27},
  doi = {10.11648/j.acis.20160402.13},
  url = {https://doi.org/10.11648/j.acis.20160402.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20160402.13},
  abstract = {This paper presents a sectored antenna array indoor positioning system (IPS) with neural network (NN) technique. The hexagonal positioning station is composed of six printed-circuit board Yagi-Uda antennas and Zigbee modules. The values of received signal strength (RSS) sensed by wireless sensors were used to be the information for object’s position estimation. Two NN models, including NN with back-propagation (BP) learning algorithm and probabilistic NN (PNN), were applied to perform the positioning work for a comparison. In the experiments, an 8x8 square meters indoor scene was performed and 288 points and 440 points were experimented in this area. The positioning results show that both NN models have the average error less than 0.7 meter. In other words, the proposed positioning system not only has the high positioning accuracy, but also has the potential in real application.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - The Sectored Antenna Array Indoor Positioning System with Neural Networks
AU  - Chih-Yung Chen
AU  - Yu-Ju Chen
AU  - Ya-Chen Weng
AU  - Shen-Whan Chen
AU  - Rey-Chue Hwang
Y1  - 2016/03/25
PY  - 2016
N1  - https://doi.org/10.11648/j.acis.20160402.13
DO  - 10.11648/j.acis.20160402.13
T2  - Automation, Control and Intelligent Systems
JF  - Automation, Control and Intelligent Systems
JO  - Automation, Control and Intelligent Systems
SP  - 21
EP  - 27
PB  - Science Publishing Group
SN  - 2328-5591
UR  - https://doi.org/10.11648/j.acis.20160402.13
AB  - This paper presents a sectored antenna array indoor positioning system (IPS) with neural network (NN) technique. The hexagonal positioning station is composed of six printed-circuit board Yagi-Uda antennas and Zigbee modules. The values of received signal strength (RSS) sensed by wireless sensors were used to be the information for object’s position estimation. Two NN models, including NN with back-propagation (BP) learning algorithm and probabilistic NN (PNN), were applied to perform the positioning work for a comparison. In the experiments, an 8x8 square meters indoor scene was performed and 288 points and 440 points were experimented in this area. The positioning results show that both NN models have the average error less than 0.7 meter. In other words, the proposed positioning system not only has the high positioning accuracy, but also has the potential in real application.
VL  - 4
IS  - 2
ER  -

Copy | Download