• Infrared and Laser Engineering
  • Vol. 51, Issue 10, 20220033 (2022)
Juncheng Sui1、2, Dengfeng Ren1、2, and Yuge Han1、2
Author Affiliations
  • 1School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
  • 2MIIT Key Laboratory of Thermal Control of Electronic Equipment, Nanjing University of Science and Technology, Nanjing 210094, China
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    DOI: 10.3788/IRLA20220033 Cite this Article
    Juncheng Sui, Dengfeng Ren, Yuge Han. Inversion and model validation method of missing parameters in infrared modeling of ground targets[J]. Infrared and Laser Engineering, 2022, 51(10): 20220033 Copy Citation Text show less

    Abstract

    The modeling of infrared radiation characteristics of ground targets requires relatively complete parameters. For non-cooperative targets, many related parameters are difficult or cannot be directly obtained by testing methods. The lack of parameters brings great difficulties to the prediction of target infrared radiation characteristics. The infrared test data of the target can be considered as the result of the comprehensive action of information including all parameters and the environment. Therefore, the test data of the target can be used to invert some important missing parameters. For cold static target, the possible missing parameters of ground target modeling are analyzed firstly, and the value ranges of the missing parameters are estimated through research and expert knowledge, etc. Based on the sensitivity theory and orthogonal experiment method, the influences of the missing parameters on target characteristics are studied, and the main missing parameters are determined, including material thickness, solar absorptivity and emissivity of the material surface. Then, based on the ground target simulation test data or measured data, combined with the conjugate gradient method, a method for inversion and model verification of ground target infrared modeling missing parameters is proposed. Finally, two examples are used to verify the method. The results show that the calculated temperature of typical measuring points after inversion of missing parameters using this method is highly consistent with the actual temperature variation characteristics, and the data error of temperature at different times does not exceed 2 K at most. The research shows that the method has good accuracy, and it can be extended and applied to the inversion of missing parameters in the infrared modeling of non-cooperative targets and the prediction of infrared radiation characteristics in the future.
    Juncheng Sui, Dengfeng Ren, Yuge Han. Inversion and model validation method of missing parameters in infrared modeling of ground targets[J]. Infrared and Laser Engineering, 2022, 51(10): 20220033
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