多目标跟踪下的无人机分布式通信决策模型

UAVs Distributed Communication Decision Model under Multi-targets Tracking

无人机组协同跟踪多目标时,需要对局部信息进行共享,以达到目标信息的准确一致,避免任务分配的冲突。常用的协同跟踪算法都假设编队的态势信息一致,但由于动态环境中噪声等不确定因素以及目标状态的动态变化,使得UAV的态势信息不一致,从而产生任务冲突,降低效率。为解决上述问题,提出一种分布式通信决策模型,利用卡尔曼滤波算法对无人机局部观测信息进行滤波处理,当局部任务分配结果与当前执行的跟踪任务产生冲突时,无人机发出通信信息,实现局部信息共享,达到态势信息的一致。仿真结果验证了改进模型的有效性。

Aiming to achieve consistent of situational awareness （SA） and avoid conflicts of task allocation, it is essential to share the local information when the multiple Unmanned Aerial Vehicle （UAV） cooperatively tracks multiple targets. The existing cooperative target tracking algorithms assume that situational information of formation is consistent. But due to the uncertain factors such as noise in the dynamic environment and the dynamic changes of the target state, the UAV＇ s SA is inconsistent, which results in task conflict and efficiency reduction. To solve this prob- lem, a distributed communication decision model is proposed. The model employs Kalman filter algorithm to process the UAV local observation information, and the UAV starts communication when the local allocation results of UAVs are conflict with the currently executing task tracking and achieve consistent of SA by sharing the local information. Simulation results show the effectiveness of the model.