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Based on the analysis of the traditional infrared target simulator calibration device, the infrared target simulator calibration device was constructed by combining three aspects of radiometric calibration theory, method and error sources, and the research on the simulation and suppression of internal spurious radiation modeling of the irradiance measurement system, the research on the infrared atmospheric transmission correction method and the research on the test result data fitting algorithm were carried out, and the compound Monte Carlo method based The mathematical model of internal spurious radiation, the calibration algorithm of infrared radiation atmospheric transmission based on the encoder-decoder structure of convolutional neural network and the algorithm of limit learning machine based on particle swarm optimization are proposed, and the irradiance metrology calibration experiments are carried out under laboratory conditions. It is verified that the accuracy of the compound Monte Carlo method is higher with equal number of tracer lines, and the standard deviation of the compound Monte Carlo method is 6.1940×10-8 with a mean error of 0.19293, and the simulation results reflect the influence of stray radiation from each part of the infrared radiometer on the stray radiation received at the incoming pupil surface of the detector; the convolutional neural network algorithm based on the encoder-decoder structure can The average error in the three bands is 3.0783%, 3.8186%, 5.3452%, which is lower than the traditional method and reduces the influence of atmospheric transmittance and atmospheric range radiation; by comparing with GA-ELM model and ELM model, it is verified that compared with the traditional data fitting method, the PSO-ELM-based method can predict the atmospheric transmittance and atmospheric range radiation in 1μm The accuracy of the PSO-ELM method is improved in the three bands of ~3μm, 3μm~5μm and 8μm~14μm, and the coefficients of determination are 0.9925, 0.9913 and 0.9814, respectively, and the average relative errors are 0.1242%, 0.7157% and 0.7471%, respectively, which effectively improve the accuracy of infrared radiation measurement.