Target tracking algorithms for multi-UAVs formation cooperative detection

This paper considers the problem of the ground target positioning and tracking algorithm for multi UAVs formation cooperative detection, and a real time and fast algorithm is proposed based on UAV airborne electro optical sensors. One state estimation problem for nonlinear stochastic system is studied by means of the unscented Kalman filter algorithm from target tracking process. To extend the single target tracking to multiple target tracking, one improved unscented Kalman filter algorithm is advised based on iterative multiple models. Furthermore, to relax the strict condition on white noise in Kalman filtering, the target tracking or state estimation is reduced to derive the inner and outer ellipsoidal approximations for the state in case of unknown but bounded noise. Finally, one simulation example confirms our theoretical results.