Cooperative guidance of multiple UAVs for target estimation based on nonlinear model predictive control

This paper presents a cooperative strategy for the salvo attack of multiple unmanned aerial vehicles (UAVs) based on one-step determinant of Fisher Information Matrix (FIM). The design aims to enhance the estimate accuracy of the target location by maximizing the FIM, which is used to measure the performance of target estimation. Considering the coupled information between each UAV and the nonlinear of kinematical equation, a nonlinear model predictive control (NMPC) is employed to derive the guidance law. To achieve salvo attack, the time-to-go error is added in the cost function of NMPC. The time-to-go estimation is obtained by the approach of Behaviour Prediction Scheme (BPS), which replicates the guidance law of virtual UAVs to simulate the behavior of the real UAVs. Numerical simulations demonstrate that the proposed approach is feasible.