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Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application

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Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application. / Mahmoud, Abdulrahman; Ahmad, Zahir; Almadani, Yousef et al.
2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). United States: IEEE, 2020. p. 1-4.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

HarvardHarvard

Mahmoud, A, Ahmad, Z, Almadani, Y, Ijaz, M, Haas, O & Rajbhandari, S 2020, Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application. in 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). IEEE, United States, pp. 1-4. https://doi.org/10.1109/CSNDSP49049.2020.9249440

APA

Mahmoud, A., Ahmad, Z., Almadani, Y., Ijaz, M., Haas, O., & Rajbhandari, S. (2020). Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application. In 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP) (pp. 1-4). IEEE. https://doi.org/10.1109/CSNDSP49049.2020.9249440

CBE

Mahmoud A, Ahmad Z, Almadani Y, Ijaz M, Haas O, Rajbhandari S. 2020. Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application. In 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). United States: IEEE. pp. 1-4. https://doi.org/10.1109/CSNDSP49049.2020.9249440

MLA

Mahmoud, Abdulrahman et al. "Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application". 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). United States: IEEE. 2020, 1-4. https://doi.org/10.1109/CSNDSP49049.2020.9249440

VancouverVancouver

Mahmoud A, Ahmad Z, Almadani Y, Ijaz M, Haas O, Rajbhandari S. Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application. In 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). United States: IEEE. 2020. p. 1-4 doi: 10.1109/CSNDSP49049.2020.9249440

Author

Mahmoud, Abdulrahman ; Ahmad, Zahir ; Almadani, Yousef et al. / Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application. 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). United States : IEEE, 2020. pp. 1-4

RIS

TY - GEN

T1 - Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application

AU - Mahmoud, Abdulrahman

AU - Ahmad, Zahir

AU - Almadani, Yousef

AU - Ijaz, Muhammad

AU - Haas, Olivier

AU - Rajbhandari, Sujan

N1 - © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Funding Information: This work is supported by Petroleum Technology Development Fund (PTDF). ; 12th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2020 ; Conference date: 20-07-2020 Through 22-07-2020

PY - 2020/11/10

Y1 - 2020/11/10

N2 - In this paper, a novel outdoor 2-D vehicular visible light positioning (VLP) using a linear array of streetlights and artificial neural network (ANN) is proposed. The classical position methods which are mostly based on triangulation will not work with the linear array of the street light. Hence, we proposed a spatial diversity receiver with ANN to overcome the collinearity condition. The proposed system is simulated for a realistic outdoor condition and provides an accurate positioning with an average RMS error of 0.53m.

AB - In this paper, a novel outdoor 2-D vehicular visible light positioning (VLP) using a linear array of streetlights and artificial neural network (ANN) is proposed. The classical position methods which are mostly based on triangulation will not work with the linear array of the street light. Hence, we proposed a spatial diversity receiver with ANN to overcome the collinearity condition. The proposed system is simulated for a realistic outdoor condition and provides an accurate positioning with an average RMS error of 0.53m.

KW - Artificial neural network

KW - outdoor positioning

KW - receiver diversity

KW - visible light positioning

U2 - 10.1109/CSNDSP49049.2020.9249440

DO - 10.1109/CSNDSP49049.2020.9249440

M3 - Conference contribution

SN - 9781728160511

SP - 1

EP - 4

BT - 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)

PB - IEEE

CY - United States

ER -