Infrared imaging recognition performance analysis using a signal-level sea surface bright band model

The growing operational demand for infrared imaging systems in maritime target detection has increased attention to the impact of sea surface bright bands on infrared recognition performance. Current analyses primarily focus on visual simulations and sea surface characterization but lack integration with imaging system performance metrics, limiting engineering applicability. This study constructs dynamic wave fields using the SWAN wave spectrum model, couples them with the MODTRAN atmospheric transmission model, and establishes a multi-component signal-level infrared radiation/reflection model for bright band analysis in engineering scenarios. Combined with the dynamic trajectories of imaging systems, mid-wave infrared (MWIR, 3–5 μm) ship image sequences under bright band interference were generated across temporal variations, solar elevation angles, and detection azimuths to analyze recognition performance. Experimental results demonstrate that when imaging systems align with the solar specular reflection axis, ship targets become fully embedded in bright bands. The high reflectivity creates a "white background-black target" negative contrast phenomenon, unexpectedly enhancing target recognition range and detection probability. As the entry azimuth deviates from the specular reflection axis, bright band interference gradually intensifies, causing recognition range attenuation. Beyond a threshold deviation angle, interference rapidly diminishes with gradual performance recovery. This study systematically analyzes the influence of sea surface bright bands on infrared recognition performance, providing critical references for optimizing entry azimuths and designing infrared anti-interference algorithms.