# A Distributed Autonomous Mission Planning Method for the Low-Orbit Imaging Constellation
## 1 Introduction  
With the improvement of satellite autonomy, the Earth Observation Satellite (EOS) has gradually become capable of onboard perception, decision-making, and inter-satellite communication, playing an increasingly important role in the field of earth observation. Along with the new control mode, EOS can perform mission planning autonomously, rather than relying solely on commands from the ground. This enables the satellite to make decisions based on its own accurate state, while responding to changes in the external environment in a more timely manner, greatly reducing the response time to target observation. At the same time, it reduces the dependence on satellite tracking, telemetry and command resources, enhancing the robustness of the overall system. In the future, with the increase in the number of autonomous EOSs, multiple autonomous EOSs together form a constellation. Then the observation mission will not only rely on a single satellite, but also rely on the cooperation of various satellites in the constellation. Determining how to improve the efficiency of the entire constellation to ensure that more tasks are scheduled in a timely, accurate and high-quality manner will be the focus of future autonomous satellite mission planning [1]. Low-orbit satellite constellations have advantages such as low latency, strong signal, global coverage, and low cost, affording them important roles in remote sensing [2, 3]. This paper focuses on the research of autonomous mission planning methods for low-orbit imaging constellations with inter-satellite links (ISLs). In the traditional satellite mission planning mode, the ground obtains the onboard status through telemetry, tracking, etc., generates the mission planning scheme, and sendsthe command to the satellite. Satellites act only as executors of instructions and do not have autonomous decision-making capabilities. In this control mode, the imaging mission planning problem can be regarded as an optimization problem. There is currently a large amount of research in this field. For example, there are exact solution algorithms such as the branch and price algorithm [4], the dynamic programming algorithm [5], meta-heuristic algorithms such as the genetic algorithm [6], adaptive large-neighborhood search algorithm [7; 8], and many heuristic algorithms [9; 10]. However, due to the long satellite-ground loop, this mode cannot respond quickly to changes in the onboard environment. As the autonomy of satellites increased, mission planning began to be combined with the autonomous capabilities of satellites. Collaboration is required in a multi-satellite environment. Two types of multi-satellite collaboration architectures are often studied: the centralized architecture and the distributed architecture. Centralized architectures usually rely on a central node that has access to all child nodes, and then performs global planning based on the collected information. For example, [PERSON] et al. [11] proposed a spacecraft constellation interaction scenario, constructing a fully centralized architecture with high-orbit satellites as master satellites and low-orbit satellites as child satellites. Master satellites receive the status information sent by the low-orbit child satellites and are responsible for the mission planning of the whole constellation. Adopting a centralized architecture has many advantages, such as less communication required and higher quality solutions. However, the centralized architecture requires high computing power of the master satellite and a good communication environment. Considering issues such as ISL failures, external interference, and communication delays, it is difficult for the master satellite to obtain information from all child satellites in a timely manner [12]. In addition, once the master satellite fails, the entire system will fall into paralysis. In order to cope with more complex communication environments and to improve system robustness, the distributed architecture is proposed.