People Counting Using IR-UWB Radar Sensor in a Wide Area

Conventional radar-based people counting systems are designed mainly for dense spatial distributions in a small region of interest (ROI). Therefore, a system with only conventional energy-based features, which are effective for a small ROI with a limited spatial distribution of individuals, generally fails to cope with the diverse and complex spatial distributions that arise from the freer movements of individuals as the ROI widens. To address this problem, a novel approach that achieves robust people counting in both wide and small ROIs is presented in this study. The proposed technique incorporates modified CLEAN-based features in the range domain and energy-based features in the frequency domain to efficiently address both dense and dispersed distributions of individuals. Subsequently, principal component analysis and an appropriate normalization of the proposed features are performed for improving the people counting system further. Based on several experiments in practical environments with wide ROIs and severe multipath effects, we observed that the proposed approach yields significantly improved performance compared with traditional people counting systems.

I. Introduction

Sensor technology plays an important role in a variety of fields as it enables systems to automatically acquire information on the surroundings [1]. Owing to the development of the Internet of Things (IoT) technology, numerous applications that use the context information from sensors have been proposed [2]–[10]. For example, in the medical field, it is possible to monitor an individual’s biological activity through sensors and, thus, prevent disease [2]–[4]. In the environmental monitoring field, the automatic detection of variations in the surroundings enables economical crop management, geological surveys, and road surveillance [5]–[7]. In future smart cities, information on the number of individuals in a certain area can facilitate efficient resource management and safety control [8]–[10].