面向对地成像观测任务的高空飞艇应急调度

针对应急条件下高空飞艇(HAA)对地成像观测任务调度问题进行研究,分析了问题中的主要约束条件,建立了以任务收益(TB)和巡航距离为优化目标的约束满足问题(CSP)模型。考虑飞艇侦察载荷具有侧摆观测能力,在构建视场范围约束模型和分辨率约束模型的基础上,对成像观测任务进行合成。提出了元任务与合成任务的概念,给出了任务合成的步骤与方法。将HAA应急调度问题转换为车辆路径问题(VRP),并进一步分解为任务排序主问题和路径选择子问题,分别应用改进粒子群(IPSO)算法和关键节点搜索(KNS)算法求解。详细介绍了算法中的编码、解码和移动等操作,以及采用的混沌初始化和禁忌搜索(TS)策略。通过仿真实验,对文中所提方法的有效性进行了验证。

Emergency Scheduling of Earth-observing Imaging Tasks on High-altitude Airships

The main constraints for the scheduling of a high-altitude airship (HAA) for imaging tasks in an emergency environment are analyzed, and a constrain satisfaction problem (CSP) model is built taking task benefit (TB) and road distance as optimization objectives. Specifically, considering the swinging capability of reconnaissance sensors, meta tasks are composed within the constraint of view coverage and resolution. In addition, this paper proposes the concepts of meta task and composite task, and then provides a composition method and its steps. The HAA scheduling task is divided into a main problem (task ranking) and a sub-problem (route choosing), which are employed in our proposed improved particle swarm optimization (IPSO) algorithm and key node search (KNS) algorithm to solve the scheduling issue. Meanwhile, such relevant operations as encoding, decoding, movement, chaos initialization and tabu search (TS) strategy, are introduced in detail. Through extensive simulation experiments, the effectiveness of the proposed algorithm is sufficiently verified.