It is of great significance to study the efficient satellite scheduling algorithm to solve the problem of unreasonable task assignment and make full use of satellite resources to collect ground information， and improve the efficiency of the Earth observation system. Aiming at the first stage pre scheduling problem of multi star distributed cooperative scheduling, the multi star scheduling problem is decomposed in the paper into a single star autonomous scheduling problem under the satellite performance and imaging constraints. In order to solve the problem, a collision imaging probability based schedule (CIPBS) algorithm is proposed by computing the real conflict coefficient, potential conflict coefficient, and energy allocation coefficient between the available time windows of the task, imaging probabilities of each task scheduling successfully by each satellite is predicted based on the distribution features of available time window, so the task assignment plan is designed to maximize the total weight of tasks that can be imaged. In this paper, three different types of task scenarios are designed to evaluate the adaptability and efficiency of the CIPBS algorithm. The experimental results show that the performance is improved by 10% to 20%.
