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一种红外目标模拟器的大气传输校准方法研究

Research on atmospheric transmission calibration method of infrared target simulator
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摘要 红外辐射在大气中传输会在大气分子、气溶胶粒子的吸收和散射以及大气自身辐射的影响下发生变化,导致红外辐射测量精度的降低。为消除大气在红外目标模拟器校准中的影响,在基于恒定标准源的宽动态红外辐射测量方法的基础上,提出了一种红外目标模拟器的大气传输校准方法。在水平均匀大气近距离的红外目标模拟器校准中,利用卷积神经网络的数据分析能力建立了不同波段、不同温度、不同距离下的大气透过率和大气程辐射的动态模型,将探测器输出电压作为基于编码器-解码器结构的卷积神经网络的输入,按照训练流程对网络进行训练,在实验环境下预测了大气传输对红外辐射的影响。所建模型能够反映大气透过率和大气程辐射的动态变化规律,并通过红外辐射反演对提出的方法进行了验证。实验结果表明:基于编码器-解码器结构的卷积神经网络算法能够较好地预测大气透过率和大气程辐射,在三个波段下的平均误差为3.0783%、3.8186%、5.3452%,低于传统方法,降低了大气透过率和大气程辐射的影响,从而减小了红外辐射的测量误差,提高了校准精度。 Objective The infrared radiometer is an important device for the calibration of the infrared target simulator and is used as a measurement transfer standard during inspections.The primary calibration parameter for the IR target simulator's radiant energy is irradiance,so the role of the IR radiometer is to measure and calibrate its outgoing irradiance.In infrared transmission,the process will be affected by the atmosphere,including two aspects:One is the infrared radiation by atmospheric molecules,aerosol particles scattered or absorbed by the attenuation,the general use of atmospheric transmittance to characterize the degree of atmospheric attenuation of infrared radiation;second is the atmosphere itself emitted by the atmospheric range of radiation will be superimposed on the target radiation.Atmospheric corrections must be made to improve calibration and measurement accuracy.Methods An atmospheric transmission calibration method for infrared target simulators is proposed based on a wide dynamic infrared radiometry method based on a constant standard source.In the calibration of the IR target simulator with a horizontal homogeneous atmospheric approach,a network model of atmospheric transmittance and atmospheric range radiation at different wavelengths,temperatures,and distances is developed using the data analysis capability of convolutional neural networks(Fig.2).Based on the encoder-decoder structure,the detector output voltage under three wavelengths is used as the input of the convolutional neural network,and the test data are normalized and input to the encoder in batches for learning and training,with the batch size set to 8 and the test distance input directly in the embedding layer,and the network is trained according to the training process(Fig.3)to obtain the test distance and atmospheric transmittance and atmospheric range,the model of radiation is given as the correspondence between them.Results and Discussions A wide dynamic infrared radiometry method based on a constant standard source was used for multiple experiments to obtain multiple detector output voltage values,which were trained using a network model(Fig.2)to obtain network output values of atmospheric transmittance and atmospheric range radiation at different distances(Fig.7).To verify the improvement of IR radiation measurement accuracy,radiation inversion is performed,and the results of radiation inversion under different methods(Fig.9)can be obtained,and the corresponding IR radiation measurement error graph(Fig.10)and specific values(Tab.2)are shown.The experimental results show that the convolutional neural network algorithm based on the encoder-decoder structure can better predict atmospheric transmittance and atmospheric path radiation,the infrared radiometric average error in three bands of the proposed method is 3.0783%,3.8186%,5.3452%,which is far lower than the traditional method,reduces the influence of atmospheric transmittance and atmospheric path radiation,reduces the measurement error of infrared radiation,and improves the calibration accuracy.Conclusions The atmospheric transmission correction algorithm is proposed for the problem of atmospheric transmission influence using the direct measurement method.Based on the wide dynamic infrared radiation measurement method with a constant standard source,a convolutional neural network algorithm based on an encoder-decoder structure is used to obtain the relationship between atmospheric transmittance,atmospheric range radiation and waveband and test distance,and atmospheric correction is performed for different wavebands and different test distances.Compared with the traditional method,there is no need to use MODTRAN software to calculate atmospheric transmittance,atmospheric range radiation and atmospheric parameters of the measurement experiment environment,which improves the problem of low distance resolution and accuracy of MODTRAN software under close measurement conditions and improves the accuracy of infrared radiation measurement.
作者 张馨怡 陈振林 Zhang Xinyi;Chen Zhenlin(Naval Aviation University,Yantai 264001,China)
机构地区 海军航空大学
出处 《红外与激光工程》 EI CSCD 北大核心 2023年第3期114-124,共11页 Infrared and Laser Engineering
关键词 大气修正 红外辐射传输 卷积神经网络 编码器-解码器 atmospheric correction infrared radiation transfer convolutional neural network encoder-decoder
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