基于微波高光谱技术的数据仿真及参数反演研究

发展高光谱微波辐射计对于提升大气参数反演精度具有重要意义。利用微波辐射传输模型mpm93以及BP 神经网络方法分别构建正演上行辐射亮温和反演大气温度廓线的模型,并研究了晴空条件下高光谱微波辐射计反演大气温度廓线的精度。54～58 GHz、64～68 GHz 在氧气吸收波段选取80 个通道作为高光谱通道,基于2015 年5～12 月昆明的探空资料进行正、反演仿真实验。选取微波成像仪/ 探测仪(SSMIS)的9 个温度探测通道进行对比实验,评估分析反演效果。实验结果表明:在大气3～10 km 高度范围内,高光谱通道的反演精度较SSMIS 提高了0.3 ～0.6 K;在0～3 km 高度范围内,反演精度提高了1 K。

Data Simulation and Parameter Inversion Based on Microwave Hyperspectral Technology

The development of hyperspectral microwave radiometers is of great significance for improving the accuracy of inversion of atmospheric parameters. In this paper, the radiant transmission model mpm93 and BP neural network are used to construct the models of forward modeling upward radiance brightness temperature and inversion of atmospheric temperature profiles, respectively, and the accuracy of inversion of atmospheric temperature profiles under the condition of clear sky by hyperspectral microwave radiometer is studied. Eighty channels are selected as the hyperspectral channels in the 54-58 GHz, 64-68 GHz oxygen absorption band, and simulation experiments are conducted based on the radiosonde data from May to December 2015 in Kunming. The nine temperature detection channels of the special sensor microwave imager/sounder (SSMIS) are selected for comparison experiments to evaluate the inversion effect. The experimental results show that the inversion accuracy of the hyperspectral channel is 0. 3-0. 6 K higher than that of the SSMIS in the altitude range of 3-10km, and the inversion accuracy is increased by 1 K in the height range of 0-3 km.