基于通信与观测联合优化的多无人机协同目标跟踪控制

Co-optimization of communication and observation for multiple UAVs in cooperative target tracking

为了提高目标跟踪任务的执行效能,提出一种基于通信与观测联合优化的多无人机协同运动目标跟踪控制方法.建立以信息成功传递概率描述的通信链路模型,采用扩展信息滤波实现目标状态融合估计与预测,使用Fisher信息矩阵对无人机观测所获取的信息进行表征.通过将信息成功传输概率引入到优化指标函数中,建立多无人机协同目标跟踪运动控制的滚动时域优化模型,实现通信与观测的联合优化,而这种联合优化体现在提高无人机与地面站之间信息成功传输概率与降低目标状态估计不确定性之间的折中.与不考虑通信优化的跟踪控制对比表明,所提方法可以提高跟踪过程中各架无人机与地面站之间的信息传输概率,使目标状态的全局融合估计结果更精确、更有效.

To improve the effectiveness of multiple unmanned aerial vehicles（UAVs） cooperative target tracking, a multi-UAVs cooperative target tracking algorithm based on co-optimization of communication and observation is presented. In the packet-erasure channel model, the probability of the successful information transmission is modeled as a function of the signal-to-noise ratio. The extended information filter is build for the estimation fusion and prediction of target states. The Fisher information matrix is applied to express the amount of information obtained from the measurements. The basis for co-optimization of communication and observation is the derivation of a scalar quantity which is a function of the expected information gain and the probability of the successful information transmission. The co-optimization of communication and observation is reflected in the tradeoffs between communication performance and sensing utility to improve overall information content delivered to the base station. Informative trajectories that maximize this metric are generated in the frame of receding horizon optimizing. Simulations demonstrate that the proposed algorithm can effectively improve the estimation performance relative to the approach that does not consider communication reliability.