DC-PHD: multitarget counting and tracking using binary proximity sensors Online publication date: Fri, 08-Dec-2023
by Nourhan T.A. Abdelnaiem; Hossam M.A. Fahmy; Anar A. Hady
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 25, No. 4, 2023
Abstract: Efficient multiple target tracking and counting have become an essential requirement for many Wireless binary Sensor Networks (WSN) applications. WSNs are inexpensive, such that sensor nodes could be easily deployed in any Area of Interest (AOI). Sensor nodes are simple, cheap and could sense the presence of a target that lies within its range. The simplest type of WSNs is the Wireless Binary Sensor Networks (WBSN), in which the deployed sensor nodes are binary. This paper investigates the problem of tracking and counting multiple individual targets that are present in a binary sensor network. An enhanced probability hypothesis density-based filter is proposed by introducing the spatial and temporal dependencies to improve the targets localisation accuracy. The implementation of dynamic counting techniques is considered to improve the efficiency of the estimations of targets trajectories. These enhancements were motivated by the failure to differentiate between multiple targets when using the PHD filtering techniques. Simulations compare the performance of the proposed algorithm with the previously mentioned target tracking approaches, to verify the efficiency and accuracy of the proposed target counting and tracking technique in binary sensor networks.
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