## 1 Introduction  
Since the beginning of the 21 st century, the competition in the global marine field has become increasingly fierce, and the maritime issues are complex and changeable. A question of how to speed up the construction of a maritime power and build a strong maritime force has become the development theme of all countries. With the development of modern information war, space has become the commanding height of reconnaissance and surveillance. The reasonable use of satellites to carry out maritime target tracking will enable the countries to take the lead in maritime military activities; thus, the maritime moving target tracking technology has become the focus of all the major countries. Compared with land-based, sea-based, and air-based detection means, space-based detection satellites have the advantages of wider coverage area, higher security, stronger concealment, and no restriction of national boundaries [1]. [PERSON] [2] defined the three phases of maritime moving target tracking as \"search, localization, and tracking\", and realized the tracking task of maritime moving targets through the scheduled planning of satellites in each task phase. [PERSON] [3] obtained the optimal moving target tracking scheme by selecting and scheduling satellite observation strips and transit windows based on a target's prior information. Automatic Identification System (AIS) assisted satellite images are used by [PERSON] [4] to design a multi-feature track association algorithm based on Iterative Closest Point (ICP) and Global Nearest Neighbor (GNN), which provide a new method for tracking moving targets at sea. [PERSON] [5] has realized the target tracking by combining satellite sequence images with information on a ship's position. A multi-channel and multi-target search method, based on reinforcement learning,was proposed by [PERSON] [6] to solve the problem of satellite searching for moving targets at sea. A nine-cell adjacent observation field of view algorithm for tracking moving targets of high-orbit satellites was designed by [PERSON] [7] to improve the utilization of the observation field of view and save a number of satellite attitude manoeuvres. The sea manoeuvring target has the characteristics of a wide range of movement and strong manoeuvrability. Due to the limitation of the orbit period of the satellite movement, the overhead imaging time cannot be controlled freely; thus, it is very difficult for space-based detection satellites to track and monitor manoeuvring targets at sea. Missing imaging opportunity may lead to the failure of the tracking task. Under this condition, if the satellite has the ability of in-orbit manoeuvring for emergency reconstruction of satellite constellation according to mission requirements, the moving target tracking task will be better completed. Furthermore, [PERSON] [8] proposed to use a \"smart satellite\" to solve the problem of tracking moving targets. [PERSON] [3] assumed that it is necessary to establish a joint scheduling technology for moving target surveillance at sea suitable for smart satellites, since the application of \"smart\" satellites increases the complexity of the scheduling problem. A manoeuvring target search strategy based on satellite reconstruction phase-modulated networking is proposed by [PERSON] [9]. [PERSON] [10] proposed to use the Biased Random Key Genetic Algorithm (BRKGA) to optimally solve the problem of moving target tracking at sea, based on satellite reconstruction. From previous studies, it can be seen that it is a popular trend to better solve the moving target observation problem using satellite constellation reconfiguration. In addition, [PERSON] [11] proposed the use of an auction algorithm for satellite constellation reconfiguration. [PERSON] [12] used genetic algorithms to optimize satellite constellation reconfiguration, while a binary certificate linear programming formulation is used by [PERSON] [13] to optimize the constellation reconstruction process.