<p>To address the scheduling challenges of mixed regional missions with different priorities across multiple observation modes of the SAR satellite, this study presents a Hierarchical Adaptive Scheduling Method (HASM) for generating optimized booting and imaging commands that align with diverse application requirements. First, considering spaceborne storage and energy limitations, a weighted multi-objective optimization model, incorporating mission decomposition and scheduling, is developed to enhance the flexibility of imaging strip segmentation and insertion. The weighted objective function is designed to balance the prioritization of urgent targets, the rapid increase of revenues, and the optimal utilization of resources. Meanwhile, the HASM method is proposed to alleviate the complexity and computational burden of high-dimensional combinatorial optimization problems. Furthermore, hyperparameters are automatically configured through observation pattern selection and optimal weight determination methods to minimize the overall mission observation time. Finally, simulation results demonstrate that the proposed method enhances the efficiency of over 95% of missions in global multi-mode mixed mission scheduling, while reducing the overall coverage time by more than 20% for China’s multi-priority missions.</p>