This study addresses the challenges in heterogeneous multi-satellite cooperative
proximity operations, including functional heterogeneity, strong temporal
coupling, and difficulties in unified planning. A functionally layered framework
composed of observation, support, and servicing satellites is constructed.
Considering the distinct mission characteristics of different satellite types,
differentiated decision variables, objective functions, and constraints are
designed, and a particle swarm optimization algorithm is employed for solution.
Simulation results demonstrate that the proposed method can generate feasible
cooperative trajectories satisfying constraints such as safety distance,
temporal coordination, communication links, and mission windows, while
maintaining system stability and operational safety. Parametric analysis
indicates that mission duration, minimum access distance, and support
effectiveness significantly affect system performance. Through functional
decomposition and cooperative optimization, the system achieves an effective
trade-off among different preferences, providing theoretical support for the
mission design and control of heterogeneous multi-satellite proximity
operations.