Abstract

The infrared radiation properties of a satellite provide essential information for space target recognition. In this study, a 3D model of a satellite is obtained using a 3D reconstruction algorithm based on deep learning. The transient temperature field distribution on the target surface is simulated using the ANSYS finite element analysis method by integrating the solar zenith angle, the position of the satellite orbit, and the dynamic angle of the detector. The infrared radiation model is used to analyze the influence of target surface temperature, orbit position, and rotation angle on infrared radiation. The calculated results show that, under the set parameters, the temperature range of all targets is 280–380 K, and the temperature distribution determines the variation trend of radiation intensity. The variation trends of radiation intensity presented by different motion postures of satellites differ considerably. The radiation intensity variation of the triaxial stabilized attitude is relatively stable, whereas the radiation intensity of the spin-stabilized attitude exhibits remarkable periodic fluctuations. The periodic motion of satellite orbit leads to periodic fluctuations in infrared radiation. The obtained infrared radiation data provide support for target detection, tracking, recognition, and infrared detector parameter design.

© 2024 Optica Publishing Group

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