We propose a method for tracking
multiple pedestrians using a binary sensor network. In our
proposed method, sensor nodes are composed of pairs of
binary sensors and placed at specific points, referred to as
gates, where pedestrians temporarily change their movement
characteristics, such as doors, stairs, and elevators,
to detect pedestrian arrival and departure events. Tracking
pedestrians in each subregion divided by gates, referred
to as microcells, is conducted by matching the pedestrian
gate arrival and gate departure events using a Bayesian
estimation-based method. To improve accuracy of pedestrian
tracking, estimated pedestrian velocity and its reliability in a
microcell are used for trajectory estimation in the succeeding
microcell. Through simulation experiments, we show that the
accuracy of pedestrian tracking using our proposed method
is improved by up to 35% compared to the conventional
method