Local positioning with artificial neural network and time of arrival technique

Hui Zhu, Bo Huang, Yuji Tanabe, Takaaki Baba

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years local positioning based on the received radio signals gets more interest. In a local environment, the multipath caused by the obstruction between transmitter and receiver are the main sources of range measurement errors, which result in the deterioration of the positioning performance. Many algorithms have been proposed for the position estimation under various environments. In this paper, an artificial neural network (ANN) based model is introduced to convert the received radio signals into position information. From the simulated results, it is indicated that the positioning precision of the proposed system, applied in a local environment, has been found to be 25% high than other algorithm under various scenarios. The implement of proposed algorithm could save the hardware cost of positioning systems.

Original languageEnglish
Title of host publication3rd International Conference on Innovative Computing Information and Control, ICICIC'08
DOIs
Publication statusPublished - 2008
Event3rd International Conference on Innovative Computing Information and Control, ICICIC'08 - Dalian, Liaoning
Duration: 2008 Jun 182008 Jun 20

Other

Other3rd International Conference on Innovative Computing Information and Control, ICICIC'08
CityDalian, Liaoning
Period08/6/1808/6/20

Fingerprint

Neural networks
Measurement errors
Deterioration
Transmitters
Hardware
Time of arrival
Costs

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Control and Systems Engineering

Cite this

Zhu, H., Huang, B., Tanabe, Y., & Baba, T. (2008). Local positioning with artificial neural network and time of arrival technique. In 3rd International Conference on Innovative Computing Information and Control, ICICIC'08 [4603698] https://doi.org/10.1109/ICICIC.2008.340

Local positioning with artificial neural network and time of arrival technique. / Zhu, Hui; Huang, Bo; Tanabe, Yuji; Baba, Takaaki.

3rd International Conference on Innovative Computing Information and Control, ICICIC'08. 2008. 4603698.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhu, H, Huang, B, Tanabe, Y & Baba, T 2008, Local positioning with artificial neural network and time of arrival technique. in 3rd International Conference on Innovative Computing Information and Control, ICICIC'08., 4603698, 3rd International Conference on Innovative Computing Information and Control, ICICIC'08, Dalian, Liaoning, 08/6/18. https://doi.org/10.1109/ICICIC.2008.340
Zhu H, Huang B, Tanabe Y, Baba T. Local positioning with artificial neural network and time of arrival technique. In 3rd International Conference on Innovative Computing Information and Control, ICICIC'08. 2008. 4603698 https://doi.org/10.1109/ICICIC.2008.340
Zhu, Hui ; Huang, Bo ; Tanabe, Yuji ; Baba, Takaaki. / Local positioning with artificial neural network and time of arrival technique. 3rd International Conference on Innovative Computing Information and Control, ICICIC'08. 2008.
@inproceedings{f931865d1dd64f4c96ecc3946f7d345c,
title = "Local positioning with artificial neural network and time of arrival technique",
abstract = "In recent years local positioning based on the received radio signals gets more interest. In a local environment, the multipath caused by the obstruction between transmitter and receiver are the main sources of range measurement errors, which result in the deterioration of the positioning performance. Many algorithms have been proposed for the position estimation under various environments. In this paper, an artificial neural network (ANN) based model is introduced to convert the received radio signals into position information. From the simulated results, it is indicated that the positioning precision of the proposed system, applied in a local environment, has been found to be 25{\%} high than other algorithm under various scenarios. The implement of proposed algorithm could save the hardware cost of positioning systems.",
author = "Hui Zhu and Bo Huang and Yuji Tanabe and Takaaki Baba",
year = "2008",
doi = "10.1109/ICICIC.2008.340",
language = "English",
isbn = "9780769531618",
booktitle = "3rd International Conference on Innovative Computing Information and Control, ICICIC'08",

}

TY - GEN

T1 - Local positioning with artificial neural network and time of arrival technique

AU - Zhu, Hui

AU - Huang, Bo

AU - Tanabe, Yuji

AU - Baba, Takaaki

PY - 2008

Y1 - 2008

N2 - In recent years local positioning based on the received radio signals gets more interest. In a local environment, the multipath caused by the obstruction between transmitter and receiver are the main sources of range measurement errors, which result in the deterioration of the positioning performance. Many algorithms have been proposed for the position estimation under various environments. In this paper, an artificial neural network (ANN) based model is introduced to convert the received radio signals into position information. From the simulated results, it is indicated that the positioning precision of the proposed system, applied in a local environment, has been found to be 25% high than other algorithm under various scenarios. The implement of proposed algorithm could save the hardware cost of positioning systems.

AB - In recent years local positioning based on the received radio signals gets more interest. In a local environment, the multipath caused by the obstruction between transmitter and receiver are the main sources of range measurement errors, which result in the deterioration of the positioning performance. Many algorithms have been proposed for the position estimation under various environments. In this paper, an artificial neural network (ANN) based model is introduced to convert the received radio signals into position information. From the simulated results, it is indicated that the positioning precision of the proposed system, applied in a local environment, has been found to be 25% high than other algorithm under various scenarios. The implement of proposed algorithm could save the hardware cost of positioning systems.

UR - http://www.scopus.com/inward/record.url?scp=52449093055&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=52449093055&partnerID=8YFLogxK

U2 - 10.1109/ICICIC.2008.340

DO - 10.1109/ICICIC.2008.340

M3 - Conference contribution

AN - SCOPUS:52449093055

SN - 9780769531618

BT - 3rd International Conference on Innovative Computing Information and Control, ICICIC'08

ER -