In view of the ever-increasing demand for satellite intelligence and the need for the fast calculation of the visible window between satellites and targets，the necessity of research on autonomous mission planning algorithms for satellites in orbit is continuously increasing.However，the traditional fixed step recursive algorithm cannot meet such requirements.In this paper，a fast optimization algorithm for the visible window of satellite-to-earth observation targets is proposed，which combines geometric methods and Newton’s dichotomy.Based on this，a multi-constraint and multi-objective autonomous task planning algorithm for optical satellites is proposed and verified by simulation.The experimental results show that the algorithm takes into account both computational efficiency and accuracy requirements.Compared with the traditional fixed step recursive algorithm，the proposed algorithm improves the calculational efficiency，keeps the accuracy from decreasing and easy to improve，and meets the requirements of multi-constraint and multi-objective scenarios.