LiDAL: Light Detection and Localization

Abstract

In this paper, we present the first indoor light-based detection and localization system that builds on concepts from radio detection and ranging (radar) making use of the expected growth in the use and adoption of visible light communication (VLC), which can provide the infrastructure for our LiDAL system. Our system enables active detection, counting and localization of people, in addition to being fully compatible with existing VLC systems. In order to detect human (targets), LiDAL uses the visible light spectrum, it sends pulses using a VLC transmitter and analyses the reflected signal collected by a photodetector receiver. Although we examine the use of the visible spectrum here, LiDAL can be used in the infrared spectrum and other parts of the light spectrum. We introduce LiDAL with different transmitter-receiver configurations and optimum detectors considering the fluctuation of the received reflected signal from the target in the presence of Gaussian noise. We design an efficient multiple input multiple output (MIMO) LiDAL system with wide field of view (FOV) single photodetector receiver, and also design a multiple input single output (MISO) LiDAL system with an imaging receiver to eliminate the ambiguity in target detection and localization. We develop models for the human body and its reflections and consider the impact of the colour and texture of the cloth used as well as the impact of target mobility. A number of detection and localization methods are developed for our LiDAL system including cross correaltion and a background subtraction method. These methods are considered to distinguish a mobile target from the ambient reflections due to background obstacles (furniture) in a realistic indoor environment.

Artificial Neural Network for LiDAL Systems

“…In this section, we introduce the configuration of the MIMO LiDAL system and the MISO IMG LiDAL system which were proposed in [33]. In addition, we present distinguishing methods namely; background subtraction method and cross correlation for mobile target distinguishing from the background obstacles (furniture).…”

“…The MIMO-LiDAL system is used to detect, count and localize targets [33]. The system consists of multiple LiDAL transmitters and multiple LiDAL receivers.…”

“…It carries out presence detection, counting, localization and tracking. In this application, people can be distinguished from the background due to their dynamic characteristics that arise from their activity (siting/standing) and motion (walking), while stationary people are undetectable [33].…”

“…In this paper, we expand the work proposed in [33] for people detection, counting and localization using LiDAL systems namely; MIMO LiDAL and MISO IMG LiDAL systems. We introduce an intelligent LiDAL system that uses artificial neural networks (ANN).…”

“…We introduce an intelligent LiDAL system that uses artificial neural networks (ANN). Based on our observations in the LiDAL systems introduced in [33], the received reflected signals in the time domain have different patterns corresponding to the number of targets and their locations in an indoor environment. The indoor environment with obstacles (furniture) appears as a set of patterns in the time domain when the transmitted optical signals are reflected from objects in MIMO LiDAL systems.…”