# A Survey of Precision Formation Relative State Measurement Technology for Distributed Spacecraft
## 4 Relative State Measurement Technology Trends and Optimization
### Multidisciplinary Optimized Architecture for Relative State-Measurement Payloads  
The distributed spacecraft formation primarily includes spacecraft members and each spacecraft formation member includes two important components: the payload and the spacecraft platform. The payload section is the distributed primary loads used to achieve the mission, such as distributed synthetic aperture radars, distributed telescopes, and relative measurement payloads to achieve formation flying. The spacecraft platform part includes the power sub-system, structure sub-system, propulsion sub-system, and control sub-system. It is responsible for carrying the payload and ensuring the reliable operation of the spacecraft in orbit [85]. Platforms and payloads complement each other, and the improvement of the relative measurement load cannot be separated from the enhancement of the comprehensive capability of the spacecraft platform [86]. However, due to competition among the subsystems, the optimization of the payload subsystem itself tends to  
Figure 31: Accuracy comparison of the relative measurement methods. compromise the performance of the platform subsystem. In order to improve the accuracy as well as the robustness of the relative measurement payload, one cannot start only from the optimization goal of the load subsystem but should instead start from the overall function of the formation. The overall design of a distributed spacecraft formation is a typical multi-disciplinary design optimization problem, with complex coupling relationships. As shown in Figure 32, this paper proposes a method architecture to select and optimize the relative measurement technologies of spacecraft, based on the overall design view of spacecraft formation flying. Under the premise of considering the disciplinary coupling and competitiveness among subsystems, such as relative measurement payloads, spacecraft platforms, and several design issues, such as formation shapes, distributed spacecraft platforms, and spacecraft loads, the differences between them should be fully considered. Multiple design goals should be effectively coordinated, constraints should be designed among distributed spacecraft subsystems, and the optimal balance point should be sought. While ensuring the overall optimization of the system, the selection analysis and optimization of the relative measurement load are completed. This approach offers distinct advantages over serial optimization methods that do not consider the coupling of other systems [87]. This provides a new approach to the relative state measurement payload optimization of distributed spacecraft formation flying in the future. The multidisciplinary design optimization method, which was first proposed by the mathematician [PERSON] in 1982, is an engineering method that can take into account the coupling of different disciplines or subsystems and that aims to solve the optimal design of complex systems [88]. It has been successfully applied to launch vehicle optimization design [86], satellite overall design [89], satellite constellation design [90; 91], etc. The overall design of the distributed spacecraft in formation flying is mainly based on the design team's initial design solutions and using manual experience; the subsystems are constantly coordinated to obtain a proposal that meets the mission requirements. The artificial experience method cannot take into account many of the constraints and coupling relationships between subsystems and cannot realize the optimization of various design schemes in a short time. This presents the shortcomings of a long cycle and a high cost [87]. This is highly unfavorable for the relative state measurement payload selection and optimization described in this paper. Therefore, for the first time, this paper proposes a multidisciplinary optimization framework to select and optimize the relative state measurement payloads of distributed spacecraft formation flying.