Encoding Space to Count Multi-Targets with Multiplexed Binary Infrared Sensors

Abstract

Recently, many researchers multiplex binary infrared sensors in object tracking, habitat monitoring, and atypical behavior detection. Due to the binary digit output of binary sensors, multiplex binary sensors may lead to count the wrong number of targets when three or more targets present in the field of interest (FOI). We call this as the invisible targets’ problem. To enhance the sensing results of sensors, a reference structure tomography technique is used to segment and code the FOI by modulating the sensing view of sensors. In this paper, we propose a subregion coding method to count targets moving in the FOI. Hexagon modulators are designed to make their projections segment the FOI into hexagon cells. We also propose a signature construct scheme to code cells and a encoder to count the number of targets in the FOI. Experiment results show that the accuracy to correctly count targets of our method is around 90% which is much better than 45% of a conventional method.