Distributed minimax filter for tracking and flocking

In this paper, we investigate a moving target tracking problem with mobile sensor networks. The moving target is assumed to be an intelligent agent, which is `smart´ enough to escape from the detection. We formulate this target estimation problem as a zero-sum game in this paper and use a so-called minimax filter to estimate the target position. The minimax filter is a robust filter that minimizes the estimation error by considering the worst case noise. Furthermore we develop a distributed version of the minimax filter for multiple sensor nodes. The distributed computation is implemented via a consensus filter. Finally, the mobile sensor nodes need to control their motions to move towards the estimated target position and avoid collisions with neighbors. A flocking algorithm is developed for this purpose. The simulation results show that the target tracking algorithm proposed in this paper provides a satisfactory result.