Complex Cloud-Sea Background Simulation for Space-Based Infrared Payload Digital Twin - Wen Sun; Yejin Li; Fenghong Li; Guangsen Liu; Peng Rao (IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing)
The advent of Industry 4.0 has highlighted the requirements for the digitization and intelligent evolution of space-based payloads. To address challenges like limited data samples and simulate infrared images in various scenarios, this study proposes a hybrid data-driven and fractal-driven cloud-sea scenario simulation approach for high-precision infrared images at space-based detection scales. Static cloud-sea scenes are generated using Qilu-2 and New Technology satellite images, while dynamic scenarios are simulated with our iterative fractal dimension optimization algorithm. Next, we propose a high-precision infrared cloud-sea simulation method based on these simulate scenarios. Finally, we validate the confidence of the simulated images through morphological assessment using a 2-D histogram and radiative accuracy evaluation based on Moderate resolution atmospheric transmission (MODTRAN) results. Experimental results confirm the method's accuracy, showing close alignment with on-orbit images. In the 2.7–3.0 μm band, our average radiance is consistent with MODTRAN. Specifically, for reflection angles below 60 $^°$ , the root mean square error between our results and MODTRAN results is about 12.3% in the 3.0–5.0 μm band, and around 3.7% in the 8.0–14.0 μm band. Morphological assessment shows an average error of about 8.3% when compared to on-orbit images. This method allows for generating multiband, multispecies, and multiscale complex cloud-sea scenario images for digital infrared payloads with high flexibility and confidence.