A lightweight target-tracking scheme using wireless sensor network

This paper describes a lightweight target-tracking scheme using wireless sensor network, where randomly distributed sensor nodes take responsibility for tracking the moving target based on the acoustic sensing signal. At every localization interval, a backoff timer algorithm is performed to elect the leader node and determine the transmission order of the localization nodes. An adaptive active region size algorithm based on the node density is proposed to select the optimal nodes taking part in localization. An improved particle filter algorithm performed by the leader node estimates the target state based on the selected nodes' acoustic energy measurements. Some refinements such as optimal linear combination algorithm, residual resampling algorithm, Markov chain Monte Carlo method are introduced in the scheme to improve the tracking performance. Simulation results validate the efficiency of the proposed tracking scheme