Distributed synchronous cooperative tracking algorithm for ground moving target in urban by UAVs

In this paper, a cooperative path planning method is proposed to track the unknown ground moving target by multiple unmanned aerial vehicles (UAVs). The kinematic UAV model with dual-input including commanded speed and heading rate is adopted, and the unknown target state is forecasted by the Extended Kalman Filter (EKF) with probability estimate. The cooperative path planning with multiple objectives and priorities is designed, where the infrastructure occlusion to line of detection sight and energy consumption are considered. Three optimisation objectives are fuzzified, and the priority is modelled by the relaxed order of satisfactory degrees. With the synchronous communication, the collision avoidance constraints and compatibility constraints under communication delay are designed. Moreover, the obstacle avoidance constraints with high buildings are addressed. Based on the distributed receding horizon control (RHC), the fuzzy multi-objective synchronous cooperative tracking model is built, and the optimal path of UAVs can be obtained by regulating the parameter. The algorithm to find the bound of regulation parameter is developed based on Karush-Kuhn-Tucker (KKT) condition. Finally, simulation results verify that the proposed method is effective and reliable.