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. ©2010 IEEE.