## 3 Proposed Methods
### Reasoning-Based Scheduling Method
#### 3.2.1 Satellite State Prediction
In a single time period of this union set, when the number of favorable targets for data transmission is greater than the number of unfavorable targets for data transmission, this period is defined as the data transmission segment and the set of data transmission segments as \(T_{d}\). Non-data transmission segment set \(T_{ud}\) is the complementary set of the non-data transmission segment \(T_{ud}=\mathbbm{C}_{T}T_{d}\). By taking the intersection of the observation segments and the data transmission segments, we have the observation-data transmission segments \(T_{od}=T_{o}\cap T_{d}\); similarly, we obtained observation-non-data transmission segments \(T_{oud}=T_{o}\cap T_{ud}\), non-observation-data transmission segments \(T_{uod}=T_{uo}\cap T_{d}\), and non-observation-non-data transmission segments \(T_{uoud}=T_{uo}\cap T_{ud}\). Next, we combined all four types of segments into a sequence and sorted them by time, and obtained the segment sequence \(Seg\). The status of each segment is defined as \(StatusSeg_{l}=od,uod,oud,uoud\), where \(l\) is the serial number of the segment. The predicted observation data volume in segment \(l\) is the observation data volume generated from the observation of predicted available targets in segment \(l\), which is expressed as  
\[\hat{M}^{l}_{in}=\sum\hat{x}_{i}\Delta t_{o}R_{cam}\hskip 14.226378 ptt_{sl} \leq t_{oi}\leq t_{el}, \tag{16}\]  
where \(t_{sl}\) and \(t_{el}\) are the start time and the end time of segment \(l\). The predicted available download data volume in segment \(l\) is calculated as  
\[\hat{M}^{l}_{out}=R_{datatrans}(t_{el}-t_{sl})\hskip 14.226378 ptStatusSeg_{l}=od \parallel uod. \tag{17}\]The cumulative value of the occupied memory capacity can be calculated as  
\[\hat{M}_{total}^{l}= \begin{cases}\max\left(\hat{M}_{in}^{l}-\hat{M}_{out}^{l},0 \right)&l=1\\ \max\left(\hat{M}_{total}^{l-1}+\hat{M}_{in}^{l}-\hat{M}_{out}^{l},0\right)&l>1 \end{cases} . \tag{18}\]  
The memory state of segment \(l\) is predicted according to the cumulative value of the occupied memory capacity using the following equation:  
\[StatusM_{l}= \begin{cases}sufficient&\hat{M}_{total}^{l}\leq M_{\max}\\ insufficient&\hat{M}_{total}^{l}>M_{\max}.\end{cases}  \tag{19}\]  
From Equation (19), we can see that when the cumulative value of the occupied memory capacity is less than the memory capacity, the memory state \(StatusM_{l}\) is _sufficient_, else, \(StatusM_{l}\), is _insufficient_. The predicted available download data volume of all the data transmission segments is expressed as  
\[\hat{M}_{outTotal}=\sum R_{datatrans}(t_{el}-t_{sl})\quad\quad StatusSeg_{l}=od \parallel uod. \tag{20}\]  
The predicted electrical energy consumption of the mission-related devices can be calculated according to the total predicted observation time and total data transmission time. The predicted electrical energy consumption includes the electrical energy consumption of mission-related devices and the normal electrical energy consumption, which can be expressed as  
\[\hat{W}_{out}=P_{cam}\left(\sum_{1}^{n_{l}}\hat{x}_{i}\Delta t_{o}\right)+P_{ datatrans}\left(\sum_{1}^{n_{l}}\hat{y}_{i}\Delta t_{d}\right)+P_{normal}(t_{e}-t_{s}). \tag{21}\]  
The predicted charging electrical power can be numerically calculated according to the satellite's attitude history, while the predicted charging electrical energy \(\hat{W}_{in}\) can be further calculated by integrating the predicted charging electrical power.