Novel decision-fusion algorithms for target tracking using ad hoc networks

In this paper we address the problem of tracking an object which moves along a certain area monitored by an ad hoc network of wireless sensors. We investigate two approaches based on the sequential Monte Carlo (SMC) methodology: an approximate version of the classical sequential importance sampling (SIS) algorithm and a recently proposed SMC methodology called cost-reference particle filtering (CRPF), which provides more flexibility in the algorithm design. Computer simulations show the feasibility and performance of the proposed methods.