基于艇载太赫兹辐射计的大气温度廊线反演

朱家玮; 周晨; 赵正予; 刘祎

doi:10.11728/cjss2025.01.2024-0069

基于艇载太赫兹辐射计的大气温度廊线反演

doi: 10.11728/cjss2025.01.2024-0069 cstr: 32142.14.cjss.2024-0069

武汉大学电子信息学院　武汉　430072

基金项目: 国家自然科学基金青年项目资助(42204161)

详细信息

作者简介:

朱家玮　2000年5月出生, 武汉大学电子信息学院硕士研究生, 主要从事临近空间环境探测方面的研究. E-mail: zzzjjw@whu.edu.cn

周晨　1983年6月出生, 武汉大学电子信息学院教授, 空间物理系副主任, 博士生导师, 长期从事空天电磁电波环境和雷达智能信号处理方面的研究. E-mail: chenzhou@whu.edu.cn

中图分类号: P414
计量
- 文章访问数: 278
- HTML全文浏览量: 87
- PDF下载量: 34
- 被引次数:
  0(来源:Crossref)
  
  0(来源:其他)
出版历程
- 收稿日期: 2024-05-17
- 修回日期: 2024-07-15
- 网络出版日期: 2024-09-09

Inversion of Atmospheric Temperature Based on THz Radiometer

School of Electronic Information, WuHan University, WuHan 430072

摘要

摘要: 基于武汉大学研制的艇载式太赫兹探测仪ATMI (Airborne THz Measure Instrument), 分析ATMI在地基与空基探测模式下对大气温度廊线的反演能力. 针对ATMI样机的硬件参数, 在空基和地基测量模式下, 建立不同纬度下大气辐射传输模型, 讨论在不同纬度下ATMI使用BP神经网络算法对于大气温度廊线的反演能力. 样机出厂后在中纬度地区进行了一个月的地基实测, 通过实测数据验证ATMI样机对于大气温度廊线反演的能力. 实测结果表明, 所研发的ATMI样机在地基反演中在0～36 km高度范围内精度优于1 K, 在一定高度范围内最高精度可优于0.3 K, 证明了所研制的艇载式太赫兹探测仪对大气温度廊线反演的有效性与准确性, 稳定度与精度达到设计指标, 显示其在太赫兹科学和临近空间环境监测中的广泛应用潜力.
- 大气温度廊线反演 /
- 艇载式太赫兹探测仪 /
- BP神经网络 /
- 大气辐射传输
Abstract: Based on the airborne terahertz detector ATMI (Airborne THz Measure Instrument) developed by Wuhan University, this paper analyzes the inversion ability of ATMI for atmospheric temperature profiles in ground-based and air-based detection modes. In view of the hardware parameters of the ATMI prototype, under air-based and ground-based measurement modes, atmospheric radiation transfer models at different latitudes are established. The inversion ability of ATMI using the BP neural network algorithm for atmospheric temperature profiles at different latitudes is discussed. After the prototype leaves the factory, one-month ground-based field measurements are carried out in mid-latitude regions. The field measurement data are used to verify the inversion ability of the ATMI prototype for atmospheric temperature profiles. The field measurement results show that for the developed ATMI prototype, in the ground-based inversion, the accuracy is better than 1 K in the altitude range of 0～36 km, and within a certain altitude range, the highest accuracy can be better than 0.3 K. This proves the effectiveness and accuracy of the developed airborne terahertz detector for the inversion of atmospheric temperature profiles. Its stability and accuracy have reached the design specifications, indicating its wide application potential in terahertz science and near-space environment monitoring.
- Atmospheric temperature profile inversion /
- ATMI /
- BPNN /
- Atmospheric radiative transfer

HTML全文

图 1 ATMI样机

Figure 1. ATMI whole machine prototype

下载: 全尺寸图片幻灯片

图 2 ATMI反演流程

Figure 2. Flow chart of the ATMI retrieval

下载: 全尺寸图片幻灯片

图 3 不同天顶角下不同高度层的RMSE

Figure 3. RMSE at different altitude layers for various zenith angles

下载: 全尺寸图片幻灯片

图 4 高中低纬地区的反演误差分布

Figure 4. Distribution of inversion errors in high, medium, and low latitude regions

下载: 全尺寸图片幻灯片

图 5 高中纬地区随高度的误差变化

Figure 5. Error variation with altitude in high, medium, and low latitude regions

下载: 全尺寸图片幻灯片

图 6 高中低纬地区一年反演数据中一天误差变化

Figure 6. Daily error variation in inversion data over one year in high, medium, and low latitude regions

下载: 全尺寸图片幻灯片

图 7 ATMI地基外场试验反演数据误差分析

Figure 7. Error analysis chart of ATMI ground-based field test inversion data

下载: 全尺寸图片幻灯片

表 1 BP 神经网络训练参数

Table 1. Training parameters of BP neural network

Parameter	Set value
Net.trainparam.epochs	10000
Net.trainparam.goal	0.01
Net.trainparam.show	1
Net.trainparam.min_grad	1×10^–6
Net.trainparam. Network_type	Elman Network
Net.trainparam. Training_function	traingdx

下载: 导出CSV

表 2 ATMI 118 GHz通道中心频点及带宽

Table 2. ATMI 118 GHz channel center frequency and bandwidth

Channel	Frequency range
1	118.75±0.08 GHz/60 MHz
2	118.75±0.2 GHz/100 MHz
3	118.75±0.4 GHz/200 MHz
4	118.75±0.8 GHz/200 MHz

下载: 导出CSV

表 3 高中低纬度地区反演误差数据指标

Table 3. Inversion error data metrics for high, medium, and low latitude regions

Area	Mean	Median	Standard deviation	Min	Max
Beijing	–1.01×10^–4	–3.62×10^–4	1.22	–10.53	11.01
Wuhan	1.93×10^–4	7.39×10^–4	1.66	–14.42	13.09
Sanya	–3.18×10^–4	–2.10×10^–3	2.11	–19.50	17.69

下载: 导出CSV

参考文献(19)

[1]	石颖. 痕量气体太赫兹临边探测辐射特性和反演算法研究[D]. 武汉: 华中科技大学, 2020. DOI: 10.27157/d.cnki.ghzku.2020.005000 SHI Ying. Research on Radiation Characteristics and Inversion Algorithms of Trace Gas Terahertz Limb Soundings[D]. Wuhan: Huazhong University of Science & Technology, 2020. DOI: 10.27157/d.cnki.ghzku.2020.005000
[2]	WANG W Y, WANG Z Z, DUAN Y Q. Preliminary evaluation of the error budgets in the TALIS measurements and their impact on the retrievals[J]. Remote Sensing, 2020, 12(3): 468 doi: 10.3390/rs12030468
[3]	王文煜. 太赫兹大气临边探测辐射计应用仿真研究[D]. 北京: 中国科学院大学(中国科学院国家空间科学中心), 2020. DOI: 10.27562/d.cnki.gkyyz.2020.000065 WANG Wenyu. Simulation Study on Application for THz Atmospheric Limb Sounder[D]. Beijing: National Space Science Center Chinese Academy of Sciences, University of Chinese Academy of Sciences, 2020. DOI: 10.27562/d.cnki.gkyyz.2020.000065
[4]	吴鹏, 李洪辉, 于雷, 等. 基于BP神经网络的大气温度廓线分层反演[J]. 科学技术创新, 2021(27): 58-59 doi: 10.3969/j.issn.1673-1328.2021.27.024 WU Peng, LI Honghui, YU Lei, et al. Hierarchical inversion of atmospheric temperature profile based on BP neural network[J]. Scientific and Technological Innovation, 2021(27): 58-59 doi: 10.3969/j.issn.1673-1328.2021.27.024
[5]	姚志刚, 陈洪滨. 利用神经网络从118.75GHz附近通道亮温反演大气温度[J]. 气象科学, 2006, 26(3): 252-259 doi: 10.3969/j.issn.1009-0827.2006.03.003 YAO Zhigang, CHEN Hongbin. Retrieval of atmospheric temperature profiles with neural network inversion of microwave radiometer data in 6 channels near 118.75 GHz[J]. Scientia Meteorologica Sinica, 2006, 26(3): 252-259 doi: 10.3969/j.issn.1009-0827.2006.03.003
[6]	SCHOEBERL M R, DOUGLASS A R, JACKMAN C H. Overview and highlights of the Upper Atmosphere Research Satellite (UARS) mission[C]//SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation. San Diego: SPIE, 1994
[7]	MERINO F, MURTAGH D P, RIDAL M, et al. Studies for the Odin sub-millimetre radiometer: III. Performance simulations[J]. Canadian Journal of Physics, 2002, 80(4): 357-373 doi: 10.1139/p01-154
[8]	RICAUD P, DE LA NOË J, ERIKSSON J E, et al. Studies for the Odin sub-millimetre radiometer. II. Retrieval methodology[J]. Canadian Journal of Physics, 2002, 80(4): 341-356 doi: 10.1139/p01-150
[9]	BARON P, OCHIAI S, DUPUY E, et al. Potential for the measurement of mesosphere and lower thermosphere (MLT) wind, temperature, density and geomagnetic field with Superconducting Submillimeter-Wave Limb-Emission Sounder 2 (SMILES-2)[J]. Atmospheric Measurement Techniques, 2020, 13(1): 219-237 doi: 10.5194/amt-13-219-2020
[10]	LIEBE H J. MPM—an atmospheric millimeter-wave propagation model[J]. International Journal of Infrared and Millimeter Waves, 1989, 10(6): 631-650 doi: 10.1007/BF01009565
[11]	DECKER M T, WESTWATER E R, GUIRAUD F O. Experimental evaluation of ground-based microwave radiometric sensing of atmospheric temperature and water vapor profiles[J]. Journal of Applied Meteorology and Climatology, 1978, 17(12): 1788-1795 doi: 10.1175/1520-0450(1978)017<1788:EEOGBM>2.0.CO;2
[12]	LÖHNERT U, MAIER O. Operational profiling of temperature using ground-based microwave radiometry at Payerne: prospects and challenges[J]. Atmospheric Measurement Techniques, 2012, 5(5): 1121-1134 doi: 10.5194/amt-5-1121-2012
[13]	王云, 王振会, 李青, 等. 基于一维变分算法的地基微波辐射计遥感大气温湿廓线研究[J]. 气象学报, 2014, 72(3): 570-582 doi: 10.11676/qxxb2014.036 WANG Yun, WANG Zhenhui, LI Qing, et al. Research of the one-dimensional variational algorithm for retrieving temperature and humidity profiles from the ground-based microwave radiometer[J]. Acta Meteorologica Sinica, 2014, 72(3): 570-582 doi: 10.11676/qxxb2014.036
[14]	陈洪滨, 林龙福. 从118.75 GHz附近六通道亮温反演大气温度廓线的数值模拟研究[J]. 大气科学, 2003, 27(5): 894-900 doi: 10.3878/j.issn.1006-9895.2003.05.10 CHEN Hongbin, LIN Longfu. Numerical simulation of temperature profile retrievals from the brightness temperatures in 6 Channels near 118.75 GHz[J]. Chinese Journal of Atmospheric Sciences, 2003, 27(5): 894-900 doi: 10.3878/j.issn.1006-9895.2003.05.10
[15]	谭泉, 姚志刚, 赵增亮, 等. 机载微波辐射计大气温湿廓线反演性能分析[J]. 气象水文海洋仪器, 2014, 31(3): 5-11 doi: 10.3969/j.issn.1006-009X.2014.03.002 TAN Quan, YAO Zhigang, ZHAO Zengliang, et al. Analysis of atmospheric parameter retrievals from airborne microwave sounding instruments[J]. Meteorological, Hydrological and Marine Instruments, 2014, 31(3): 5-11 doi: 10.3969/j.issn.1006-009X.2014.03.002
[16]	张容容. 基于BP神经网络的多通道微波辐射计大气参数反演算法[D]. 武汉: 华中科技大学, 2017 ZHANG Rongrong. Retrieval Method of Multichannel Ground-Based Microwave Radiometer for Atmospheric Parameters Based on BP Neural Network[D]. Wuhan: Huazhong University of Science & Technology, 2017
[17]	关鑫. 大气温度廓线高光谱微波探测技术研究[D]. 成都: 电子科技大学, 2021. DOI: 10.27005/d.cnki.gdzku.2021.002507 GUAN Xin. Research on Hyperspectral Microwave Detection Technology of Atmospheric Temperature Profile[D]. Chengdu: University of Electronic Science and Technology of China, 2021. DOI: 10.27005/d.cnki.gdzku.2021.002507
[18]	李书磊, 刘磊, 高太长. 大气辐射传输模拟器(ARTS)软件的介绍[J]. 大气与环境光学学报, 2016, 11(4): 241-248 LI Shulei, LIU Lei, GAO Taichang. Introduction of atmospheric radiative transfer simulator software[J]. Journal of Atmospheric and Environmental Optics, 2016, 11(4): 241-248
[19]	邹荣士, 何文英, 王普才, 等. 辐射传输模式对地基微波辐射计观测亮温的模拟能力分析[J]. 大气科学, 2021, 45(3): 605-616. doi: 10.3878/j.issn.1006-9895.2008.20134 ZOU Rongshi, HE Wenying, WANG Pucai, et al. Assessment of radiative transfer models based on observed brightness temperature from ground-based microwave radiometer[J]. Chinese Journal of Atmospheric Sciences, 2021, 45(3): 605-616 doi: 10.3878/j.issn.1006-9895.2008.20134