Health Assessment of Unmanned Aerial Vehicle Formation Systems under False Data Injection Attack

Abstract

This paper proposes a method for health assessment of unmanned aerial vehicle formation system under false data injection attack. The models of unmanned aerial vehicle and false data injection attack are built, and leader-follower structure is adopted for the formation system. The degree of health reflecting the probability that the error exceeds its allowable value subject to random noise and false data injection attack is established. Derivation of the degree of health is formulated as an optimization problem and procedures to solve the optimization problem are also provided. Finally, simulation is carried out to depict the dynamics of a unmanned aerial vehicle formation system under false data injection attack with the degree of health of the system highlighted.