TY - JOUR A2 - Su, Housheng AU - Ma, Liang AU - Xue, Kai AU - Wang, Ping PY - 2015 DA - 2015/09/08 TI - Distributed Multiagent Control Approach for Multitarget Tracking SP - 903682 VL - 2015 AB - In multiagent systems, tracking multiple targets is challenging for two reasons: firstly, it is nontrivial to dynamically deploy networked agents of different types for utility optimization; secondly, information fusion for multitarget tracking is difficult in the presence of uncertainties, such as data association, noise, and clutter. In this paper, we present a novel control approach in distributed manner for multitarget tracking. The control problem is modelled as a partially observed Markov decision process, which is a NP-hard combinatorial optimization problem, by seeking all possible combinations of control commands. To solve this problem efficiently, we assume that the measurement of each agent is independent of other agents’ behavior and provide a suboptimal multiagent control solution by maximizing the local Rényi divergence. In addition, we also provide the SMC implementation of the sequential multi-Bernoulli filter so that each agent can utilize the measurements from neighbouring agents to perform information fusion for accurate multitarget tracking. Numerical studies validate the effectiveness and efficiency of our multiagent control approach for multitarget tracking. SN - 1024-123X UR - https://doi.org/10.1155/2015/903682 DO - 10.1155/2015/903682 JF - Mathematical Problems in Engineering PB - Hindawi Publishing Corporation KW - ER -