## 4 Key Technology  
### Data Fusion  
It is mentioned in the first section that pure data-driven PHM has three shortcomings, and data fusion can compensate for two of them. Data fusion is a technique that uses telemetry data to drive models to produce reliable simulation data, which is then supplemented by simulation data. The simulation data supplement the telemetry data in two dimensions. One is the time dimension. Due to the existence of areas without communication links, the telemetry data of satellites cannot be obtained for a long time in these areas during each orbital cycle. However, the simulation data produced by data fusion can fill the vacancy during this period, so as to realize the monitoring of satellites for the whole time period. Second is the quantity dimension. Due to the limitation of the transmission bandwidth and number of sensors, the telemetry data of the constellation are limited. It is likely that the variables measured by sensors are less sensitive to fault characteristics. However, the simulation data do not have such restrictions. All variables involved in the model can be directly obtained. Therefore, data fusion can extend the input dimension of fault data to achieve more accurate fault detection and diagnosis.  
To achieve data fusion, it is necessary to build a bridge between the digital model and the physical entity and to establish a two-way mapping relationship between them. After the construction of the constellation, the ground control center is responsible for the direct monitoring and control of the constellation operation and is the data source of telemetry data. As shown in the left of Figure 7, a satellite in the constellation establishes a connection with the ground control center through TCP/IP or UDP protocol. It parses the source code of the subscription data frame and injects it into the digital model to drive the synchronization of models. Together with the telemetry data, the simulation data provide data support for health management services at the upper layer.  
The process of data fusion is shown in the right of Figure 7. According to the characteristics of the data, the telemetry data are classified into two categories, namely, environmental parameters and status parameters. In order to ensure that the environment of the constellation model is consistent with that of the physical entity, environmental parameters, such as solar light intensity, solar incident angle and orbital information, need to be injected into the digital model at each simulation step, while for status parameters, such as equipment power consumption, bus voltage and current, temperature inside the device, attitude angle and attitude angle velocity of satellites, it is sufficient to inject them as the initial state in the first simulation step, and the subsequent simulation values are derived from the model principles. As the simulation time progresses, the error between the simulation data and telemetry data will gradually accumulate until the preset threshold is exceeded, the O&M personnel manually or the system automatically injects the telemetry values of the above state parameters into the model again in the area with communication to synchronize the state of the model and the physical entity and ensure the accuracy of the simulation data.