面向应急对地观测任务的多平台资源部署优化研究

提出了一种基于遗传算法的面向应急对地观测任务的多平台资源部署优化方法。该方法通过把观测区域离散化为网格点的集合,将多平台资源部署问题形式化为一个组合优化问题,其目标是在一定响应时间约束下最大化观测区域覆盖率。设计的求解算法采用整数编码表示各平台资源的部署位置,使用精英保留策略加快算法收敛速度。仿真结果表明,该方法能够快速获得满意的卫星、飞艇、无人机多平台资源部署方案。

Research on Optimization Deployment Approach of Multi-Platform Resources for Emergency Earth Observation Tasks

For emergency earth observation tasks, an approach for deploying multi-platform resources based on genetic optimization is proposed in this paper. We model the observation area into the grids, formulate the multi-platform resource deployment as a combination optimization problem, which has the goal of maximizing the cover probability of the observation area in the constraint of a cestain response time. Integer encoding is adopted in the approach to represent the positions of resources. Besides, elitism strategy is applied to improve the convergence rate. Simulation results demonstrate that the approach can achieve satisfactory multi-platform resources deployment solution, including satellite, airship and UAV(Unmanned Aerial Vehicle).