Sensor attack avoidance: Linear quadratic game approach

For reliable and sustainable decision making, it is essential to perform intelligent sensing and data collection at scalable network resources costs. The sensor platforms used in a warfare may be under attacks from adversarial forces, which will largely impact the overall performance of surveillance systems. Thus, it is crucial that each intelligent sensor have the capability of detecting and avoiding possible attacks. In this paper, we study an attack-avoidance problem under the framework of a LQ game formulation. This is a first attempt to solve such kind of problems. From a practical point of view, the inherent hard constraints have been approximated and replaced by soft constraints with a fixed optimization horizon. For implementation, a receding horizon scheme has been used in junction with the LQ strategies. Overall, the LQ strategies can provide good control guidance laws for the players.