Ground target tracking using acoustic sensors

In this paper the tracking of ground targets using acoustic sensors, distributed in a wireless network, is studied. The solution to the tracking problem is given within the Bayesian recursive framework. A particle filter (PF) is developed which includes a data association technique based on joint probabilistic data association (JPDA) and a method for handling road constraints. Validation and evaluation of the tracking algorithms are performed using real data extracted from a ground sensor network. The tracking of the targets shows a satisfactory result.