To address the challenges posed by highly time-sensitive targets with uncertainty and unpredictability in multi-satellite cooperative observation, conventional intelligent optimization algorithms often suffer from time-consuming and unstable issues. This paper presents a novel dynamic mission planning method that cleverly incorporates waiting time for tracking and tracked time as heuristics to guide task assignment. Furthermore, plannable and robustness indicators are introduced to facilitate global trade-offs in resource conflicts among multiple targets. Initially, the constraints specifically suitable for time-sensitive target observation are analyzed, followed by the modeling of the planning problem. Subsequently, a dynamic mission planning approach is proposed that utilizes dynamic priorities, offering a linear time solution for task assignment. Through simulation verification, the efficacy of the proposed method is demonstrated, showcasing its ability to enhance multi-satellite cooperative observation effectively. Additionally, it maximizes resource utilization in the face of diverse conflicts.