Tracking of hypersonic glide vehicles (HGVs) by a constellation tracking and observation system is an important part of the space-based early warning system. The uncertainty in the maneuver intentions of HGVs has a non-negligible impact on the tracking and observation process. The cooperative scheduling of multiple satellites in an environment of uncertainty in the maneuver intentions of HGVs is the main problem researched in this paper. For this problem, a satellite constellation tracking decision method that considers the HGVs’ maneuver intentions is proposed. This method is based on building an HGV maneuver intention model, developing a maneuver intention recognition and prediction algorithm, and designing a sensor-switching strategy to improve the local consensus-based bundle algorithm (LCBBA). Firstly, a recognizable maneuver intention model that can describe the maneuver types and directions of the HGVs in both the longitudinal and lateral directions was designed. Secondly, a maneuver intention recognition and prediction algorithm based on parallel, stacked long short-term memory neural networks (PSLSTM) was developed to obtain maneuver directions of the HGV. On the basis of that, a satellite constellation tracking decision method (referred to as SS-LCBBA in the following) considering the HGVs’ maneuver intentions was designed. Finally, the maneuver intention prediction capability of the PSLSTM network and two currently popular network structures: the multilayer LSTM (M-LSTM) and the dual-channel and bidirectional neural network (DCBNN) were tested for comparison. The simulation results show that the PSLSTM can recognize and predict the maneuver directions of HGVs with high accuracy. In the simulation of a satellite constellation tracking HGVs, the SS-LCBBA improved the cumulative tracking score compared to the LCBBA, the blackboard algorithm (BM), and the variable-center contract network algorithm (ICNP). Thus, it is concluded that SS-LCBBA has better adaptability to environments with uncertain intentions in solving multi-satellite collaborative scheduling problems.

In this study, differential game theory was applied to propose two guidance laws of a pursuer in an orbit pursuit–evasion–defense game. One was a conservative guidance law of maneuvering to absolute safety before pursuing the evader, and the other was a radical guidance law of playing with the defender only when necessary. Both guidance laws enable the pursuer to avoid the defender while pursuing the evader, but the radical guidance law reduces the pursuit time by moving the pursuer closer to the defender. The pursuer, defender, and evader are all spacecraft carrying three-axis thrusters that can provide independent thrust in three directions. The proximity dynamics processes of the participants were described by the Clohessy–Wiltshire equations. A method for solving the time-to-go analytically was proposed by simplifying the dynamics model to meet real-time requirements. The effectiveness of the two guidance laws was verified by numerical simulations, and the differences between the two laws were analyzed.