We investigate cooperative target tracking of multiple unmanned aerial vehicles (UAVs) with a limited communication range. This is an integration of UAV motion control, target state estimation, and network topology control. We first present the communication topology and basic notations for network connectivity, and introduce the distributed Kalman consensus filter. Then, convergence and boundedness of the estimation errors using the filter are analyzed, and potential functions are proposed for communication link maintenance and collision avoidance. By taking stable target tracking into account, a distributed potential function based UAV motion controller is discussed. Since only the estimation of the target state rather than the state itself is available for UAV motion control and UAV motion can also affect the accuracy of state estimation, it is clear that the UAV motion control and target state estimation are coupled. Finally, the stability and convergence properties of the coupled system under bounded noise are analyzed in detail and demonstrated by simulations.

我们研究了通信范围有限的多种无人机的协作目标跟踪。这是无人机运动控制，目标状态估计和网络拓扑控制的集成。我们首先介绍网络连接的通信拓扑和基本符号，然后介绍分布式卡尔曼共识滤波器。然后，分析了使用滤波器的估计误差的收敛性和有界性，并提出了潜在的函数来维护通信链路和避免冲突。通过考虑稳定的目标跟踪，讨论了基于分布式势函数的无人机运动控制器。由于只有目标状态的估算而不是状态本身可用于无人机运动控制，并且无人机运动也会影响状态估算的准确性，显然，无人机运动控制和目标状态估计是耦合的。最后，详细分析了耦合系统在有限噪声下的稳定性和收敛性，并通过仿真进行了验证。