### The Distributed Task Planning Algorithm  
The mission planning algorithms of the satellite constellation tracking system primarily include centralized [28; 29; 30] and distributed planning [31; 32]. All tasks in centralized task planning are scheduled by a main controller. The main controller needs to collect information from all satellites and provide planning solutions for them. The communication lag and delayed responsiveness in the real time limit centralized mission planning restrict its ability to adapt to the trajectories of highly maneuverable HGVs.  
Distributed task planning algorithms include multi-agent task planning algorithms [33; 34; 35; 36], auction-based planning algorithms [37], and consensus-based planning algorithms [38; 39; 40]. Among these, the consensus-based task planning algorithms have superior planning results and the fastest convergence [38]. The LCBBA is a mature and well-performing consensus algorithm [41]. The first two of these groups of methods require the selection of the information hub satellite in the constellation. Each satellite exchanges information with the information hub satellite to negotiate a planning solution. The consensus-based mission planning algorithm does not have an information hub and a main controller. In order to reach the global goal eventually, each satellite in the constellation needs to follow the same process, including self-evaluation, the satisfaction of local constraints, communication, and cooperation [42]. Considering the dynamic nature of the satellite's own state information and mission information in the actual mission, there are differences in the state information of other satellites collected by each satellite. Therefore, the LCBBA considers a local consensus based on the consensus-based bundle algorithm (CBBA) [41], which is suitable for the actual situation in satellite constellation tracking systems.  
During the relay tracking of a target by two satellites, the reassigned satellite needs to choose a suitable time to continue tracking the target before the previous satellite ends its observation. The target's trajectory varies with time and has a high degree of uncertainty. A satellite's visibility of the target is affected by the uncertainty of the target trajectory and affects the selection of the handover satellite and handover time. Therefore, it is necessary to consider the uncertainty of the target trajectory in the mission decision method. Previously, a cooperative task scheduling algorithm to handle multiple autonomous satellite systems was proposed [35]. The algorithm was designed with a dynamic-distributed structure and a single-satellite scheduling algorithm that balances the robustness and stability of the system. The algorithm was also applied to two autonomous coordination mechanisms, the improved contact network protocol (ICNP) and the blackboard model (BM), and useful conclusions were obtained. In addition, adding the robustness parameter to the value function is a way to improve the ability of the LCBBA to adapt to the target's uncertainty. In this paper, we consider the uncertainty of the maneuver intentions of HGVs and add an uncertainty factor to the value function of the satellite-independent decision. Sensor-switching strategies are then designed to accommodate the effects of target maneuvers on satellite visibility.