Digital Imaging Simulation and Closed-Loop Verification Model of Infrared Payloads in Space-Based Cloud–Sea Scenarios

Driven by the rising demand for digitalization and intelligent development of infrared payloads, next-generation systems must be developed within compressed timelines. High-precision digital modeling and simulation techniques offer essential data sources but often falter in complex space-based scenarios due to the limited availability of infrared characteristic data, hindering evaluation of the payload effectiveness. To address this, we propose a digital imaging simulation and verification (DISV) model for high-fidelity infrared image generation and closed-loop validation in the context of cloud–sea target detection. Based on on-orbit infrared imagery, we construct a cloud cluster database via morphological operations and generate physically consistent backgrounds through iterative optimization. The DISV model subsequently calculates scene infrared radiation, integrating radiance computations with an electron-count-based imaging model for radiance-to-grayscale conversion. Closed-loop verification via blackbody radiance inversion is performed to confirm the model’s accuracy. The mid-wave infrared (MWIR, 3–5 µm) system achieves mean square errors (RSMEs) < 0.004, peak signal-to-noise ratios (PSNRs) > 49 dB, and a structural similarity index measure (SSIM) > 0.997. The long-wave infrared (LWIR, 8–12 µm) system yields RMSEs < 0.255, PSNRs > 47 dB, and an SSIM > 0.994. Under 20–40% cloud coverage, the target radiance inversion errors remain below 4.81% and 7.30% for the MWIR and LWIR, respectively. The DISV model enables infrared image simulation across multi-domain scenarios, offering vital support for optimizing on-orbit payload performance.