Passive Sensor Based Multiple Objects Tracking and Association Method in Wireless Sensor Networks

Abstract

This article presents a method for dynamic data association in wireless sensor networks and addresses the issue of multiple objects tracking. The sensor node used in this article incorporates RFID reader and an acoustic sensor so that two different signals are cooperating for tracking and associating multiple objects. The RFID tag is used for object identification and an acoustic sensor is used for estimating object movements. In the heterogeneous sensor networks, our proposed association method is analyzed with association success, failure, and recovery cases. In addition, 2-dimensional (2D) particle filtering is used for estimating a objects state such as position and velocity. The performance is compared between a single sensor node and multiple sensor nodes in our proposed algorithm. In addition, the association performance with multiple sensor nodes is evaluated as a function of sampling time and object movement behavior. Finally, the effect of the two heterogeneous sensors range difference is analyzed and discussed.