Abstract: ‍ ‍Angle track association algorithm aims to correctly associate trajectories observed by different sensors based on principle of identity， it is one of the core and difficult problems of space-based optical surveillance system. Its performance directly determines the target tracking performance of space-based optical surveillance system. In the dense multi-target scene， target overlap occurs frequently affected by sensor resolution， the point diffusion effect of the optical system and target occlusion. Current algorithms achieve good performance in most scenes， but they can not deal with the problem of association between one angle track and multiple angle tracks caused by occlusion and unresolved targets， it is no longer satisfies the one-to-one association assumption， and current algorithms achieve poor performance. Current algorithms satisfy the one-to-one assumption and achieve poor performance in the case of occlusion and unresolved targets. To solve this problem， this paper proposes an algorithm based on traversal of the feasibility matrix. The algorithm takes the hinge angle difference as the statistic and considers all the possible association assignments， and calculates the probability of each possible association event， and the final association result is calculated based on Bayesian criterion. Simulation results show that the algorithm can effectively deal with the situation that multiple targets share an angle track caused by occlusion and unresolved of target， and has better adaptability to complex multi-target scenes.