Indoor Intruder Tracking Using Visible Light Communications

Farah Mahdi Yaseen Al Sallami; Zahir Ahmad; Stanislav Zvanovec; Paul Anthony  Haigh; Olivier Haas; Sujan Rajbhandari

doi:10.3390/s19204578

Indoor Intruder Tracking Using Visible Light Communications

Farah Mahdi Yaseen Al Sallami, Zahir Ahmad, Stanislav Zvanovec, Paul Anthony Haigh, Olivier Haas, Sujan Rajbhandari

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

57 Downloads (Pure)

Abstract

This paper proposes a comprehensive study of indoor intruder tracking using visible light communication (VLC). A realistic indoor VLC channel was developed, taking into consideration reflections, shadowing, and ambient noise. The intruder was considered smart and aiming to escape tracking. This was modelled by adding noise and disturbance to the intruder’s trajectory. We propose to extend the application of minimax filtering from state estimation in the radio frequency (RF) domain to intruder tracking using VLC. The performance of the proposed method was examined and compared with Kalman filter for both VLC and RF. The simulation results showed that the minimax filter provided marginally better tracking and was more robust to the adversary behavior of the intruder than Kalman filter, with less than 0.5 cm estimation error. In addition, minimax was significantly better than Kalman filter for RF tracking applications.

Original language	English
Article number	4578
Number of pages	14
Journal	Sensors
Volume	19
Issue number	20
DOIs	https://doi.org/10.3390/s19204578
Publication status	Published - 21 Oct 2019

Bibliographical note

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Keywords

Indoor VLC channel
Intruder tracking
Kalman filter
Minimax filter
State estimation
Visible light communication

ASJC Scopus subject areas

Analytical Chemistry
Biochemistry
Atomic and Molecular Physics, and Optics
Instrumentation
Electrical and Electronic Engineering

Access to Document

10.3390/s19204578Licence: CC BY

PublishedFinal published version, 2.41 MBLicence: CC BY

Cite this

@article{bec665af35094f628caafb37152e1583,

title = "Indoor Intruder Tracking Using Visible Light Communications",

abstract = "This paper proposes a comprehensive study of indoor intruder tracking using visible light communication (VLC). A realistic indoor VLC channel was developed, taking into consideration reflections, shadowing, and ambient noise. The intruder was considered smart and aiming to escape tracking. This was modelled by adding noise and disturbance to the intruder{\textquoteright}s trajectory. We propose to extend the application of minimax filtering from state estimation in the radio frequency (RF) domain to intruder tracking using VLC. The performance of the proposed method was examined and compared with Kalman filter for both VLC and RF. The simulation results showed that the minimax filter provided marginally better tracking and was more robust to the adversary behavior of the intruder than Kalman filter, with less than 0.5 cm estimation error. In addition, minimax was significantly better than Kalman filter for RF tracking applications.",

keywords = "Indoor VLC channel, Intruder tracking, Kalman filter, Minimax filter, State estimation, Visible light communication",

author = "{Al Sallami}, {Farah Mahdi Yaseen} and Zahir Ahmad and Stanislav Zvanovec and Haigh, {Paul Anthony} and Olivier Haas and Sujan Rajbhandari",

note = "This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).",

year = "2019",

month = oct,

day = "21",

doi = "10.3390/s19204578",

language = "English",

volume = "19",

journal = "Sensors",

issn = "1424-3210",

publisher = "MDPI",

number = "20",

}

TY - JOUR

T1 - Indoor Intruder Tracking Using Visible Light Communications

AU - Al Sallami, Farah Mahdi Yaseen

AU - Ahmad, Zahir

AU - Zvanovec, Stanislav

AU - Haigh, Paul Anthony

AU - Haas, Olivier

AU - Rajbhandari, Sujan

N1 - This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

PY - 2019/10/21

Y1 - 2019/10/21

N2 - This paper proposes a comprehensive study of indoor intruder tracking using visible light communication (VLC). A realistic indoor VLC channel was developed, taking into consideration reflections, shadowing, and ambient noise. The intruder was considered smart and aiming to escape tracking. This was modelled by adding noise and disturbance to the intruder’s trajectory. We propose to extend the application of minimax filtering from state estimation in the radio frequency (RF) domain to intruder tracking using VLC. The performance of the proposed method was examined and compared with Kalman filter for both VLC and RF. The simulation results showed that the minimax filter provided marginally better tracking and was more robust to the adversary behavior of the intruder than Kalman filter, with less than 0.5 cm estimation error. In addition, minimax was significantly better than Kalman filter for RF tracking applications.

AB - This paper proposes a comprehensive study of indoor intruder tracking using visible light communication (VLC). A realistic indoor VLC channel was developed, taking into consideration reflections, shadowing, and ambient noise. The intruder was considered smart and aiming to escape tracking. This was modelled by adding noise and disturbance to the intruder’s trajectory. We propose to extend the application of minimax filtering from state estimation in the radio frequency (RF) domain to intruder tracking using VLC. The performance of the proposed method was examined and compared with Kalman filter for both VLC and RF. The simulation results showed that the minimax filter provided marginally better tracking and was more robust to the adversary behavior of the intruder than Kalman filter, with less than 0.5 cm estimation error. In addition, minimax was significantly better than Kalman filter for RF tracking applications.

KW - Indoor VLC channel

KW - Intruder tracking

KW - Kalman filter

KW - Minimax filter

KW - State estimation

KW - Visible light communication

UR - http://www.scopus.com/inward/record.url?scp=85073744682&partnerID=8YFLogxK

U2 - 10.3390/s19204578

DO - 10.3390/s19204578

M3 - Article

SN - 1424-3210

VL - 19

JO - Sensors

JF - Sensors

IS - 20

M1 - 4578

ER -

Indoor Intruder Tracking Using Visible Light Communications

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Olivier haas

Cite this

Indoor Intruder Tracking Using Visible Light Communications

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Profiles

Olivier haas

Cite this