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 journalArticle

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 languageEnglish
Article number4578
Number of pages14
JournalSensors
Volume19
Issue number20
DOIs
Publication statusPublished - 21 Oct 2019

Fingerprint

optical communication
Radio
Kalman filters
Light
radio frequencies
Noise
State estimation
state estimation
Error analysis
Trajectories
escape
disturbances
Visible light communication
trajectories
filters
simulation

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

Cite this

Indoor Intruder Tracking Using Visible Light Communications. / Al Sallami, Farah Mahdi Yaseen; Ahmad, Zahir; Zvanovec, Stanislav; Haigh, Paul Anthony ; Haas, Olivier; Rajbhandari, Sujan.

In: Sensors, Vol. 19, No. 20, 4578, 21.10.2019.

Research output: Contribution to journalArticle

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