面向编目维持与扩展的天基光学主被动 任务规划方法研究

To address the dual requirements of catalog maintenance for large-scale targets and efficient search for new born objects in space situational awareness systems， a task planning method for space-based optical sensors with active passive collaboration is proposed. Wide field-of-view passive detection sensors are adopted to conduct wide-area search， which enhances the discovery capability of new-born targets and simultaneously maintains the states of cataloged targets within the field of view. Narrow field-of-view active detection sensors carry out task planning based on the birth time and state covariance of targets， thus realizing accurate observation scheduling for newly discovered targets and key targets with high state uncertainty. The observation information acquired by each sensor is processed by the labeled multi-Bernoulli （LMB） filter to achieve high-precision state estimation of large-scale space targets. A multi-sensor information fusion method considering the label matching mechanism of new-born targets is designed， which improves the discovery efficiency and state estimation accuracy of new-born targets while ensuring the continuous and accurate state estimation of large-scale space targets. Simulation experiments verify the good effectiveness and adaptability of the proposed method in complex space surveillance environments.