关键词: 区域目标观测, 敏捷卫星, 多条带观测, 六边形网格, 双层优化框架

Abstract: Agile satellites possess both roll and pitch maneuverability and can employ a strip-mosaicking observation mode for regional target imaging, thereby improving coverage efficiency. In this multiple-strip observation scheduling process, the roll angle, pitch angle, and the start and end times of each observation strip must be jointly optimized, which greatly increases problem complexity. To address this, we propose a grid-tessellation-based scheduling method for regional target observation with agile satellites. First, a hexagonal grid is used to perform two-level discretization of the target area for coverage quantification, attitude mapping, and heuristic guidance. Second, a nonlinear mixed-integer programming model is formulated to maximize coverage under multiple constraints. To solve the model, we design a bilevel optimization framework with adaptive feedback iteration and develop a bilevel algorithm that integrates simulated annealing with a cooperative particle swarm–genetic method. The upper level allocates observation strips via simulated annealing with multi-neighborhood strategies, while the lower level plans pitch angles and observation windows using the coopera-tive particle swarm–genetic algorithm. Extensive comparative experiments show that, in agile-satellite regional observation scenarios, the proposed approach achieves higher coverage and more stable convergence than alternative upper- and lower-level baselines. Fur-thermore, compared with traditional Earth observation modes, the strip-mosaicking strategy significantly increases regional coverage.

Key words: Regional target observation, Agile satellite, Multiple-strip observation, Hexagonal grid, Bi-level optimization framework