# On-Board Ship Detection in Micro-Nano Satellite Based on Deep Learning and COTS Component
## 3 Construction of Computing Platform in Micro-Nano Satellite  
### The Integrated Information Flow of Platform and Payload  
Micro-nano satellites refer to small satellites weighing less than 100 kg, such as SkySat, Flock-1 and so on. In 2017, 467 spacecrafts were launched around the world, of which 321 were micro-nano satellites (68.7%). A large amount of data for earth observation can be generated by micro-nano satellites, and these data will be downlinked when the satellites fly over the ground stations, which is not time-sensitive. Besides, the limited bandwidth of satellite-earth data transmission leads to many valuable images not downlinked to ground. This situation significantly limits the application ability of micro-nano satellites.  
To alleviate the pressure of data transmission, the remote sensing image can be simplified by some on-board processing on the satellites. The small size of the configuration brings a variety of resource limitations on micro-nano satellites, such as power consumption, energy, computing power and so on. Therefore, it is difficult to achieve advanced tasks. At present, traditional on-board processing tasks are mainly focused on image preprocessing, mass data storage and format conversion, data compression, automatic analysis of original data and target feature extraction, etc. With the improvement of spatial resolution of remote sensing image and the sharp increase of data volume, it not only forms data basis for the higher information processing on the satellite, but also brings challenges to the performance, flexibility, power consumption and other aspects of the on-board processing technology.  
The integrated information flow of platform and payload is an effective method to improve the capacity of imaging and processing for micro-nano satellites. The technology has the advantages of improving the location precision for remote sensing image, reducing satellite quality, and reducing construction cost. We use heterogeneous backup of System on Chip (SoC) and Graphic Processing Unit (GPU) to meet the demand of the integration of information flow. SoC is utilized to achieve satellite platform and payload management and control with high reliability, including remote metering, remote control, attitude and orbit control, time management, payload management, recovery processing, etc. GPU with high-performance data processing capability is applied to do on-orbit real-time remote sensing image processing. Besides, the satellite can use the CPU embedded in the GPU processing module as the backup of SoC, not only ensure that satellite platform safe and reliable, but also meet the requirements of on-board high performance computing.  
Figure 5 shows the hardware architecture of the integrated information flow. The information flow is interacted through CAN bus and satellite affairs, measurement, navigation and other functions are controlled through integrated information flow unit. The imaging of remote sensing payload unit is adjusted by integrated energy flow unit and attitude control unit, and then remote sensing images are transmitted to GPU and satellite-ground communication unit through camera link respectively. Target patches and information processed by GPU are transmitted to the satellite-ground communication unit through LVDS and then satellite-ground communication unit transmits these data to the ground receiver by antenna. The micro-nano satellite needs to choose the type of data (images or patches and information) with the limitation of the downlink capability.