  In this paper, we introduce an intelligent light detection and localization
(LiDAL) system that uses artificial neural networks (ANN). The LiDAL systems of
interest are MIMO LiDAL and MISO IMG LiDAL systems. A trained ANN with the
LiDAL system of interest is used to distinguish a human (target) from the
background obstacles (furniture) in a realistic indoor environment. In the
LiDAL systems, 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 background obstacles
(furniture) appears as a set of patterns in the time domain when the
transmitted optical signals are reflected from objects in LiDAL systems. Hence,
a trained neural network that has the ability to classify and recognize the
received signal patterns can distinguish the targets from the background
obstacles in a realistic environment. The LiDAL systems with ANN are evaluated
in a realistic indoor environment through computer simulation.
