Liu Lianwei, Dong Shikui, Chen Qianrong, Zou Qianjin, Fan Hongjie, Qu Dongsheng. Infrared radiation imaging calculation of aerial target based on CUDA parallel computing[J]. Infrared and Laser Engineering, 2020, 49(4): 0404003-0404003-7. DOI: 10.3788/IRLA202049.0404003
Citation: Liu Lianwei, Dong Shikui, Chen Qianrong, Zou Qianjin, Fan Hongjie, Qu Dongsheng. Infrared radiation imaging calculation of aerial target based on CUDA parallel computing[J]. Infrared and Laser Engineering, 2020, 49(4): 0404003-0404003-7. DOI: 10.3788/IRLA202049.0404003

Infrared radiation imaging calculation of aerial target based on CUDA parallel computing

  • A GPU parallel computing method for infrared target imaging was established, in which skin and plume was included. The SLG model was used to calculate the infrared characteristics of the radiation gases, and the LOS method was used to solve the infrared radiation transmission equation of the plume. According to the imaging geometry relationship between the surface and the three-dimensional plume, a target projection algorithm was established, in the method the forward ray tracing method was used to calculate the surface radiation imaging, and the reverse ray tracing method was used to calculate the plume radiation imaging. The CUDA parallel method was used to increase the calculation speed in the skin projection calculation module and the plume radiation calculation module, and the fast calculation of the target infrared spectrum image at the entrance of the detector was realized. The results show that the projection imaging algorithm can accurately generate the target image under the set conditions. The radiation distribution of the target infrared image is consistent with the temperature distribution. The calculation result of the tail flame radiation intensity is in good agreement with the experimental results. The CUDA parallel algorithm can effectively improve the computational efficiency of the program, the calculation speed of the skin projection module can be more than hundred times when the amount of calculation is large.
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