# On-Board Ship Detection in Micro-Nano Satellite Based on Deep Learning and COTS Component
## 6 Discussion  
Many experiments in Section 5 verify the validity of the proposed scheme. We can use the Jetson TX2 as a part of integrated information flow unit in micro-nano satellite and achieve on-board ship detection algorithm through the unit. Figure 8 illustrates an example for the result of our scheme. The red boxes are the detection results of our ship detection method and the white boxes are the target patches extracted by our network. The two numbers are the image coordinates of the central point for each ships and they will be converted into geographic coordinates through coordinate conversion. The target patches and geographic coordinates are transmitted to the ground receivers. As shown in Figure 8, our scheme has good performance both in detection and patch quality and the results verify the effectiveness of strategies in our scheme. The file size of the image is 90.6 MB while the target patches and information are 810 KB in total. The reduction in file size is the biggest advantage of on-board ship detection, which helps to alleviate the pressure of satellite-ground mutual transmission and ground receivers.  
For some emergencies, the ground users can control several micro-nano satellites in networking or constellation to obtain the raw remote sensing images over the areas focused on. Then the on-board ship detection algorithm is applied to extract the target patches and information from these raw remote sensing images. Finally, the target patches and information are transmitted to the ground user by relay satellites or other methods in a short time, which can improve the response speed to emergencies. Some perceptually lossless compression methods can be used to achieve image compression for target patches, which can further reduce the file size of target patches. The ground users can make better decisions to deal with emergencies by these valuable data. For other cases, the micro-nano satellites downlink the raw remote sensing images to the ground when the satellites fly over the ground stations. The raw data can be used for other purposes.  
To achieve other on-board tasks, the users should store the programs and models in the integrated information flow unit on the ground. During the micro-nano satellites operating in orbit, the programs and models for new tasks can also be updated or uploaded to the satellite through the satellite upload channel. The micro-nano satellites can achieve many on-board intelligent processing tasks by the computing platform proposed in our scheme, which greatly improves the application ability of micro-nano satellites.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Indexes** & **Test Results in Laboratory** \\ \hline
**Cost** & \$599 \\
**Weight** & \$5 g \\
**Size** & \$50 mm \(\times\) 87 mm \\
**Power** & \$3\(\sim\)5 W (peak: 15 W) \\
**Temperature** & \(<\)45 \({}^{\circ}\)C \\
**Computing capability** & 1 TFLOPS \\
**Model size** & 108.03 MB \\
**Processing time** & 1.25 s (1 K \(\times\) 1 K) \\ \hline \hline \end{tabular}
\end{table}
Table 5: The indexes of Jetson TX2 tested in laboratory.