Compared to a single UAV with limited sensing coverage and communication capability, multi-UAV cooperation is able to provide more effective sensing and transmission (S&T) services. Nevertheless, most existing works on multi-UAV sensing mainly focus on mutually exclusive task allocation and independent data transmission, which did not fully exploit the benefit of multi-UAV sensing and communication. Motivated by this, we propose a novel multi-UAV cooperative S&T scheme with replicated sensing task allocation. Although replicated task allocation may sound counter-intuitive, it can actually foster cooperative transmission among multiple UAVs and thus reduce the overall sensing mission completion time. To obtain the optimal task allocation and transmit power of the proposed scheme, a mission completion time minimization problem is formulated. To solve this problem, a necessary condition for replicated sensing task allocation is derived. For the cases of replicated sensing, the considered problem is transformed into a monotonic optimization and is solved by the generic Polyblock algorithm. To efficiently evaluate the mission completion time in each iteration of the Polyblock algorithm, new auxiliary variables are introduced to decouple the otherwise sophisticated joint optimization of transmission time and power. While for the degenerated case of non-replicated sensing, the closed-form expression of the optimal transmission time is derived
翻译:与遥感覆盖面和通信能力有限的单一无人驾驶航空器相比,多无人驾驶航空器合作能够提供更有效的遥感和传输(S&T)服务,然而,多数现有的多无人驾驶航空器遥感工作主要侧重于相互排斥的任务分配和独立数据传输,这些任务分配和独立数据传输没有充分利用多无人驾驶航空器遥感和通信的好处,因此,我们提出一个新的多无人驾驶航空器合作S&T计划,采用复制的遥感任务分配办法。虽然复制的任务分配可能听上去是反直觉的,但实际上可以促进多个无人驾驶航空器之间的合作传输,从而缩短整个遥感任务完成时间。为获得最佳任务分配和传送拟议计划的权力,制定了任务完成时间最小化问题。为解决这一问题,提出了复制任务分配任务的必要条件。对于复制的遥感来说,所考虑的问题已转变成一个单一的优化,由通用的聚块算法解决。为高效评估聚块算法每次反复计算的任务完成时间,引入新的辅助变量,以解析本来复杂的联合传输时间和权力的联合优化。同时,对非复制式变式变式的超式传输情况进行最佳的转换。