Laboratory spectral calibration of TanSat and the influence of multiplex merging of pixels

ABSTRACT This article first reviews the main characteristics of the High-Resolution Hyperspectral Sensor for carbon observation Grating Spectrometer (HRHS-GS) and discusses the impact of spectral resolution on gas absorption lines. The major content of this article is the laboratory calibration of HRHS-GS, the signal-to-noise ratio (SNR), instrument line shape (ILS), and the spectral resolution of each channel were achieved. The SNR results met the mission requirements for the 0.76 µm band, but missed the requirement for the two Carbon dioxide (CO2) bands. To address this problem, the model ‘Multiplex Merging of Spectral Pixels’ was established to improve the SNR by increasing the incident energy of a single spectral channel. This process would lead to spectral broadening; the spectral resolution before and after that process was obtained. The transmittance spectra before and after multiplex merging were compared by the line-by-line radiative transfer model (LBLRTM) to analyse the impact of spectral broadening on gas absorption lines. Next, the results were verified by experiment with a gas absorption cell. The results showed that ‘Multiplex Merging of Spectral Pixels’ could effectively improve the SNR. For the 0.76 µm band, the transmittance spectra before and after multiplex merging were almost the same; for the 1.61 µm band, the peak value of the transmittance spectra decays by about 5%; and for the 2.06 µm band, the attenuation of the transmittance spectra is smaller than 3%. Meanwhile, the spectral resolution after spectral broadening still satisfied the study’s requirement.

[1]  David Crisp,et al.  Measuring atmospheric carbon dioxide from space with the Orbiting Carbon Observatory-2 (OCO-2) , 2015, SPIE Optical Engineering + Applications.

[2]  Charles E. Miller,et al.  NASA Orbiting Carbon Observatory: measuring the column averaged carbon dioxide mole fraction from space , 2008 .

[3]  K. G. Gribanov,et al.  Testing forward model against OCO-2 and TANSO-FTS/GOSAT observed spectra in near infrared range , 2015, Atmospheric and Ocean Optics.

[4]  Changxiang Yan,et al.  Cloud and aerosol polarimetric imager , 2014, Photoelectronic Technology Committee Conferences.

[5]  Olga B. Rodimova,et al.  Continuum water vapor absorption in the 4000–8000cm-1 region , 2015, Atmospheric and Ocean Optics.

[6]  陈. C. Bo,et al.  Radiation calibration of EUV space cameras , 2016 .

[7]  邢廷文 Xing Tingwen,et al.  Infrared dual band athermal optical system with common aperture , 2016 .

[8]  Stefan Sinzinger,et al.  An imaging spectrometer employing tunable hyperchromatic microlenses , 2016, Light, science & applications.

[9]  Son Thai Le,et al.  Real-time high-resolution heterodyne-based measurements of spectral dynamics in fibre lasers , 2016, Scientific Reports.

[10]  吴荣华,et al.  星载近红外高光谱CO 2 遥感进展 , 2015 .

[11]  李志刚 李志刚 High accuracy spectroradiometric standard light source based on detector standard , 2015 .

[12]  David Crisp,et al.  Preflight Radiometric Calibration of the Orbiting Carbon Observatory , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[13]  A. Ozcan,et al.  Pixel super-resolution using wavelength scanning , 2015, Light: Science & Applications.

[14]  翟岩 Zhai Yan,et al.  Focal plane alignment and testing for an off-axis multispectral space borne camera , 2016 .

[15]  Samuele Del Bianco,et al.  Comparison of Column-Averaged Volume Mixing Ratios of Carbon Dioxide Retrieved From IASI/METOP-A Using KLIMA Algorithm and TANSO-FTS/GOSAT Level 2 Products , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[16]  David Crisp,et al.  The Orbiting Carbon Observatory (OCO-2): spectrometer performance evaluation using pre-launch direct sun measurements , 2014 .

[17]  Ralph R. Basilio,et al.  OCO-2 (Orbiting Carbon Observatory-2) mission operations planning and initial operations experiences , 2014, SPIE Remote Sensing.

[18]  S. Boland,et al.  High precision atmospheric CO2 measurements from space: The design and implementation of OCO-2 , 2012, 2012 IEEE Aerospace Conference.

[19]  颜昌翔 Yan Chang-xiang,et al.  Optical remote sensor for cloud and aerosol from space:past, present and future , 2015 .

[20]  任建伟 Ren Jian-wei,et al.  Spectral and radiometric calibrations for mapping satellite-1 camera , 2015 .

[21]  E. R. Polovtseva,et al.  The HITRAN2012 molecular spectroscopic database , 2013 .

[22]  Yi Liu,et al.  Analysis of XCO2 retrieval sensitivity using simulated Chinese Carbon Satellite (TanSat) measurements , 2013, Science China Earth Sciences.

[23]  李宪圣 Li Xian-sheng,et al.  Influence factors on SNR of TDICCD space camera , 2015 .

[24]  Rebecca Castano,et al.  Atmospheric validation of high accuracy CO2 absorption coefficients for the OCO-2 mission , 2012 .

[25]  David M. Rider,et al.  OCO/GOSAT Preflight Cross-Calibration Experiment , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[26]  David M. Rider,et al.  Preflight Spectral Calibration of the Orbiting Carbon Observatory , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[27]  Sami Ur Rehman,et al.  SNR improvement for hyperspectral application using frame and pixel binning , 2016, SPIE Asia-Pacific Remote Sensing.

[28]  Y. Liu,et al.  Chinese Carbon Dioxide Satellite (TanSat) Status and Plans , 2012 .

[29]  Graeme L. Stephens,et al.  Sensitivity analysis of polarimetric O 2 A-band spectra for potential cloud retrievals using OCO-2/GOSAT measurements , 2015 .

[30]  Tomoyuki Urabe,et al.  The instrumentation and the BBM test results of thermal and near-infrared sensor for carbon observation (TANSO) on GOSAT , 2006, SPIE Optics + Photonics.