Volume 52 Issue 4
Apr.  2023
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Ma Xiuxiu, Wang Haiyan, Han Qijin, Zhang Xuewen, Zhao Hang, Xu Zhaopeng, Zeng Jian, Ma Lingling, Wang Ning. On-board calibration and verification of GF5B thermal infrared channel[J]. Infrared and Laser Engineering, 2023, 52(4): 20220644. doi: 10.3788/IRLA20220644
Citation: Ma Xiuxiu, Wang Haiyan, Han Qijin, Zhang Xuewen, Zhao Hang, Xu Zhaopeng, Zeng Jian, Ma Lingling, Wang Ning. On-board calibration and verification of GF5B thermal infrared channel[J]. Infrared and Laser Engineering, 2023, 52(4): 20220644. doi: 10.3788/IRLA20220644

On-board calibration and verification of GF5B thermal infrared channel

doi: 10.3788/IRLA20220644
Funds:  National Key Research and Development Program of China (2019YFE0127300); Strategic Priority Research Program of the Chinese Academy of Sciences (XDA26010201-3)
  • Received Date: 2023-01-25
  • Rev Recd Date: 2023-02-15
  • Available Online: 2023-04-14
  • Publish Date: 2023-04-25
  •   Objective   Thermal infrared remote sensing has the ability of day and night detection and good environmental adaptability, which makes it have important applications in natural ecological environment monitoring, urban heat island effect monitoring, lake and reservoir water quality monitoring, etc. The application of thermal infrared remote sensing has gradually changed from qualitative to quantitative, and absolute radiometric calibration is the prerequisite for the quantification of remote sensing information. Among them, on-board blackbody calibration uses on-board blackbody as the calibration source, which is not limited by time, environment and other factors. It can produce corresponding calibration coefficients for each orbit data, improve the frequency of on-orbit absolute radiometric calibration. Based on the on-board 0-level blackbody calibration data of GF5B VIMI (Hyperspectral observation satellite, visible and infrared multispectral image), the absolute radiometric calibration research of satellite thermal infrared channel is carried out. In this way, reliable calibration results can be obtained to provide a method basis for the subsequent blackbody calibration of satellite thermal infrared remote sensing.  Methods   Based on the laboratory calibration before the launch of GF5B satellite, the on-board blackbody calibration data is used to establish the on-board absolute radiometric calibration model applicable to the GF5B thermal infrared channel. Firstly, relative radiometric correction is carried out for the high and low temperature blackbody image data transmitted from satellite; based on the blackbody image data after relative radiation correction, the average DN of each channel corresponding to the high and low temperature blackbody is obtained. At the same time, the high and low blackbody temperature is calculated based on the high and low temperature blackbody auxiliary data, and then the radiance value of the corresponding channel of the high and low temperature blackbody is calculated using the Planck function. Then, according to the actual response average DN of the high and low temperature blackbody image and the corresponding channel radiance, the inner blackbody absolute radiometric calibration coefficient is calculated. Finally, the internal and external blackbody calibration conversion coefficients are used to convert the internal calibration coefficients into the absolute radiometric calibration coefficients of the on-board blackbody (Fig.1). In addition, according to the error sources of the on-board calibration system, various indicators affecting the accuracy of the on-board calibration system are analyzed. The accuracy of on-board blackbody calibration is evaluated and verified by using the ground synchronous buoy measurement data.  Results and Discussions  The on-board blackbody calibration data of the 1 850th orbit on January 12, 2022 are selected to conduct the on-board blackbody absolute radiometric calibration, and its on-board absolute radiometric calibration coefficient (Tab.3) is obtained. Through the analysis of various indicators affecting the accuracy of the on-board radiometric calibration system, the results show that the total error of the on-board radiometric calibration of the camera is 1.268% (Tab.4), and the equivalent temperature is 299.1 K@300 K. Therefore, the absolute calibration accuracy of the on-board calibration system is 0.9 K. The verification results of satellite-ground synchronization show that the relative differences of radiance of B11 and B12 channels are 0.64% and 1.35% respectively. The brightness temperatures of B11 channel monitored by satellite and ground measurements are 273.78 K and 273.45 K respectively, with a difference of 0.33 K; the brightness temperatures of B12 channel monitored by satellite and ground measurements are 272.58 K and 273.35 K respectively (Tab.5), with a difference of 0.77 K, which shows that the brightness temperature difference is within 0.8 K. The satellite-ground data have a good consistency, which indicates that the thermal infrared channel of GF5B satellite has a high calibration accuracy on orbit, and the results are true and reliable.  Conclusions   The on-board blackbody calibration method based on GF5B thermal infrared channel has good accuracy and reliable calibration results, which can meet the needs of remote sensing data quantification application. It provides a method reference for real-time and accurate acquisition of thermal infrared channel calibration coefficient. The construction of the research method is based on GF5B on-board calibration blackbody, which has important reference value for the on-board blackbody calibration of other satellites.
  • [1] Chen Muwang, Qi Hongxing, Gong Yumei, et al. Analysis of effect of calibration blackbody temperature stability on the infrared imaging [J]. Infrared and Laser Engineering, 2006, 35(6): 652-654. (in Chinese)
    [2] Li Xiaoman, Zhao Yanhua, Ma Wenpo. Analysis of the means to improve the temperature sensitivity of thermal IR remote sensing system [J]. National Remote Sensing Bulletin, 2021, 25(8): 1655-1660. (in Chinese)
    [3] Anderson M C, Allen R G, Morse A, et al. Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources [J]. Remote Sensing of Environment, 2012, 122: 50-65.
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    [6] Kustas W, Anderson M. Advances in thermal infrared remote sensing for land surface modeling [J]. Agricultural and Forest Meteorology, 2009, 149(12): 2071-2081. doi:  10.1016/j.agrformet.2009.05.016
    [7] Susana D P, Pablo R, David H, et al. Vicarious radiometric calibration of a multispectral camera on board an unmanned aerial system [J]. Remote Sensing, 2014, 6(3): 1918-1937. doi:  10.3390/rs6031918
    [8] Sun Ke, Fu Qiaoyan, Qi Xueyong. Radiometric cross-calibration of thermal infrared channel of IRS sensor on HJ-1B satellite [J]. Infrared and Laser Engineering, 2010, 39(5): 785-790. (in Chinese)
    [9] Xu Heyu, Zhang Liming, Huang Wenxin, et al. On-board absolute radiometric calibration and validation based on solar diffuser of HY-1C SCS [J]. Acta Optica Sinica, 2020, 40(9): 0928002. (in Chinese)
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    [12] Dinguirard M, Slater P N. Calibration of space-multispectral imaging sensors: A review [J]. Remote Sensing of Environment, 1999, 68(3): 194-205. doi:  10.1016/S0034-4257(98)00111-4
    [13] Teillet P M, Slater P N, Ding Y, et al. Three methods for the absolute calibration of the NOAA AVHRR sensors in-flight [J]. Remote Sensing of Environment, 1990, 31(2): 105-120. doi:  10.1016/0034-4257(90)90060-Y
    [14] Teillet P M, Markham B L, Irish R R. Landsat cross-calibration based on near simultaneous imaging of common ground targets [J]. Remote Sensing of Environment, 2006, 102(3-4): 264-270. doi:  10.1016/j.rse.2006.02.005
    [15] Han Qijin, Min Xiangjun, Fu Qiaoyan, et al. Analysis of onboard calibration accuracy of HJ-1B infrared multispectral camera [J]. Spacecraft Recovery & Remote Sensing, 2010, 31(3): 41-47. (in Chinese)
    [16] Sheng Yicheng, Dun Xiong, Jin Weiqi, et al. Review of on-orbit radiometric calibration technology used in infrared remote sensors [J]. Infrared and Laser Engineering, 2019, 48(9): 0904001. (in Chinese)
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On-board calibration and verification of GF5B thermal infrared channel

doi: 10.3788/IRLA20220644
  • 1. China Center for Resources Satellite Data and Application, Beijing 100094, China
  • 2. China Siwei Surveying and Mapping Technology Co. Ltd., Beijing 100094, China
  • 3. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Fund Project:  National Key Research and Development Program of China (2019YFE0127300); Strategic Priority Research Program of the Chinese Academy of Sciences (XDA26010201-3)

Abstract:   Objective   Thermal infrared remote sensing has the ability of day and night detection and good environmental adaptability, which makes it have important applications in natural ecological environment monitoring, urban heat island effect monitoring, lake and reservoir water quality monitoring, etc. The application of thermal infrared remote sensing has gradually changed from qualitative to quantitative, and absolute radiometric calibration is the prerequisite for the quantification of remote sensing information. Among them, on-board blackbody calibration uses on-board blackbody as the calibration source, which is not limited by time, environment and other factors. It can produce corresponding calibration coefficients for each orbit data, improve the frequency of on-orbit absolute radiometric calibration. Based on the on-board 0-level blackbody calibration data of GF5B VIMI (Hyperspectral observation satellite, visible and infrared multispectral image), the absolute radiometric calibration research of satellite thermal infrared channel is carried out. In this way, reliable calibration results can be obtained to provide a method basis for the subsequent blackbody calibration of satellite thermal infrared remote sensing.  Methods   Based on the laboratory calibration before the launch of GF5B satellite, the on-board blackbody calibration data is used to establish the on-board absolute radiometric calibration model applicable to the GF5B thermal infrared channel. Firstly, relative radiometric correction is carried out for the high and low temperature blackbody image data transmitted from satellite; based on the blackbody image data after relative radiation correction, the average DN of each channel corresponding to the high and low temperature blackbody is obtained. At the same time, the high and low blackbody temperature is calculated based on the high and low temperature blackbody auxiliary data, and then the radiance value of the corresponding channel of the high and low temperature blackbody is calculated using the Planck function. Then, according to the actual response average DN of the high and low temperature blackbody image and the corresponding channel radiance, the inner blackbody absolute radiometric calibration coefficient is calculated. Finally, the internal and external blackbody calibration conversion coefficients are used to convert the internal calibration coefficients into the absolute radiometric calibration coefficients of the on-board blackbody (Fig.1). In addition, according to the error sources of the on-board calibration system, various indicators affecting the accuracy of the on-board calibration system are analyzed. The accuracy of on-board blackbody calibration is evaluated and verified by using the ground synchronous buoy measurement data.  Results and Discussions  The on-board blackbody calibration data of the 1 850th orbit on January 12, 2022 are selected to conduct the on-board blackbody absolute radiometric calibration, and its on-board absolute radiometric calibration coefficient (Tab.3) is obtained. Through the analysis of various indicators affecting the accuracy of the on-board radiometric calibration system, the results show that the total error of the on-board radiometric calibration of the camera is 1.268% (Tab.4), and the equivalent temperature is 299.1 K@300 K. Therefore, the absolute calibration accuracy of the on-board calibration system is 0.9 K. The verification results of satellite-ground synchronization show that the relative differences of radiance of B11 and B12 channels are 0.64% and 1.35% respectively. The brightness temperatures of B11 channel monitored by satellite and ground measurements are 273.78 K and 273.45 K respectively, with a difference of 0.33 K; the brightness temperatures of B12 channel monitored by satellite and ground measurements are 272.58 K and 273.35 K respectively (Tab.5), with a difference of 0.77 K, which shows that the brightness temperature difference is within 0.8 K. The satellite-ground data have a good consistency, which indicates that the thermal infrared channel of GF5B satellite has a high calibration accuracy on orbit, and the results are true and reliable.  Conclusions   The on-board blackbody calibration method based on GF5B thermal infrared channel has good accuracy and reliable calibration results, which can meet the needs of remote sensing data quantification application. It provides a method reference for real-time and accurate acquisition of thermal infrared channel calibration coefficient. The construction of the research method is based on GF5B on-board calibration blackbody, which has important reference value for the on-board blackbody calibration of other satellites.

    • 由辐射理论可知,任何大于绝对零度的物体都会向外辐射能量,地球表面辐射的波谱主要集中在热红外波段8~14 μm的光谱区,可见热红外遥感可以获取更丰富的目标信息。热红外遥感昼夜探测的能力以及良好的环境适应性使其在自然生态环境监测、军事侦察、城市热岛效应监测、水源地及湖库水质监测、灾害评估等方面有着重要且广泛的应用[1-3]。这些领域的遥感应用逐渐由定性走向定量化,绝对辐射定标是遥感信息定量化的前提,也是采用遥感信息研究建立各种遥感模型和反演地表参数的基础[4-6],定义为传感器输出量(一般为观测图像计数值DN)与目标输入绝对物理量之间的定量关系。

      光学遥感器绝对辐射定标方法有发射前实验室定标和发射后在轨定标,其中,在轨定标主要包括星上定标、场地定标和交叉定标等[7-8]。实验室定标不能完全模拟太空环境,无法准确预估卫星传感器在轨运行期间的性能,且发射升空后的卫星会因外部环境变化、传感器老化及灵敏度下降等问题而造成遥感器辐射特性产生变化,为保证卫星对地观测数据的可靠性和定量化应用水平,需要对其进行在轨绝对辐射定标[9-11]。场地定标和交叉定标受时间、天气条件、地表环境、空间分辨率及光谱差异等因素限制,定标周期长,定标精度受限[12-14]。星上黑体定标采用星载黑体作为定标的标定源,不受时间、环境等因素限制,可针对每轨数据生产相应的定标系数,连续监测传感器的探测性能,从而提高在轨绝对辐射定标的频率,是实现光学遥感器星上高频次、高效率、高精度的手段之一[15-16]

      为了满足不断发展的热红外定量化应用需求,我国于2021年9月7日在太原卫星发射中心成功发射了高光谱观测卫星(GF5B),又称为高分五号02星。作为太阳同步轨道卫星,GF5B的轨道高度为705 km,卫星平台搭载两台对地观测载荷(可见短波红外高光谱相机、全谱段光谱成像仪)和五台大气监测载荷(大气主要温室气体监测仪、大气痕量气体差分吸收光谱仪、大气气溶胶多角度偏振探测仪、高精度偏振扫描仪和吸收性气溶胶探测仪)以及数传分系统。全谱段光谱成像仪(Visible and infrared multispectral imager,VIMI)共有12个波段,其中,B11~B12波段为热红外窗口通道:B11(10.30~11.30 μm)、B12 (11.40~12.50 μm),星下点空间分辨率40 m,量化等级12 bit,幅宽为60 km,红外波段可通过平台搭载的星上黑体来实现星上绝对辐射定标。

      文中基于GF5B VIMI载荷星上0级黑体定标数据,开展卫星热红外通道的绝对辐射定标研究。通过星上定标数据处理,得到成像仪各通道的绝对辐射定标系数,进而对星上定标系统进行精度分析,并基于烟台浮标实测数据对计算的星上定标系数进行验证,以期获取可靠的定标结果,为后续卫星热红外遥感器星上黑体定标提供方法依据。

    • GF5B VIMI载荷以推扫方式成像,相机扫描镜每扫描过地物条带一行,光学系统就会对定标黑体观测一次,对于每一条扫描线,扫描镜先记录定标黑体的辐射值,然后扫描地面。卫星在轨运行时,通过高温黑体和低温黑体实现星上绝对辐射定标。热红外星上黑体绝对辐射定标模型如图1所示,首先对星上下传高低温黑体图像数据进行相对辐射校正,基于相对辐射校正后黑体图像数据获取得到高低温黑体对应各通道的平均响应灰度值(DN);同时,基于星上下传高低温黑体辅助数据计算高低温黑体温度,进而采用普朗克函数计算高低温黑体对应通道辐亮度值;然后,根据星上高低温黑体图像实际响应平均灰度值及对应通道辐亮度值,计算得到内黑体绝对辐射定标系数;最后,采用内外黑体定标转换系数,将内定标系数转换为星上黑体绝对辐射定标系数。

      Figure 1.  Absolute radiometric calibration process of thermal infrared on-board blackbody

    • 当相机入瞳处的入射光照完全均匀一致时,由于各种因素的影响,各个探测元输出的灰度值并不完全相同,为了纠正这种偏差,需要对图像进行相对辐射校正,从而消除由于探测器在空间上的响应不一致、在时间上的不稳定性以及电路噪声所引起的非均匀性辐射失真。采用两点法对星上下传黑体定标数据进行相对辐射校正,将各探测元在高低温黑体对应辐亮度下的原始灰度值分别校正到所有探测元的平均灰度值[17]。校正方程如公式(1)所示:

      式中:DNcal为探测元校正后灰度值;DNraw为探测元原始灰度值;i为探测元;k为校正增益;b为校正偏移量。

      其中,各探测元的校正系数计算方法如公式(2)所示:

      式中:$ {\overline {DN} _h} $$ \overline {D{N_l}} $分别为高低温黑体对应辐亮度下所有探测元的平均灰度值;$D{N_h}(i)$$D{N_l}(i)$分别为高低温黑体对应辐亮度下第i个探测元的平均灰度值。

    • 基于相对辐射校正后的黑体定标数据,分别提取高温黑体和低温黑体的平均灰度值,如公式(3)所示:

      式中:$\overline {DN} $为黑体的平均灰度值;DNcali)为相对辐射校正后第i个像元灰度值;n为像元总数。

    • 温度控制盒下传高温黑体及低温黑体相关温度测量值为电压值,分系统管理控制器收到后需将其转换为温度,如公式(4)所示:

      式中:T为黑体温度值,单位为K;R为热敏电阻,单位为Ω;A0A1A2为热敏电阻系数。其中,热敏电阻R的计算方法如公式(5)所示:

      式中:Rp为分压电阻值(10000 Ω);a = 5/32 768,为分层值;N为源码。

    • 成像仪的入瞳等效光谱辐亮度采用公式(6)进行计算[7]

      式中:Le为入瞳等效光谱辐亮度,单位W·m−2·sr−1·μm−1L为光谱辐亮度;ε 为发射率;Rλ)为成像仪的光谱响应函数,GF5B VIMI热红外通道B11~B12的光谱响应函数如图2所示。

      Figure 2.  GF5B B11-B12 channel spectral response curve

      其中,黑体温度与光谱辐亮度两者之间的转换关系采用普朗克函数进行计算[18],如公式(7)所示:

      式中:T为黑体的绝对温度,单位为K;λ为波长,单位为μm;c1 = 3.7415×108 W·m−2·μm4c2 = 1.43879×104 μm·K。

    • 相机在轨工作时,内定标黑体的等效光谱辐亮度不是成像仪入瞳处的等效光谱辐亮度,需建立内定标方程和外定标方程的转换关系,进而计算出与内定标黑体温度对应的入瞳等效光谱辐亮度,为在轨利用内定标方程建立绝对辐射定标方程提供数据[19],其中内外黑体定标系数由实验室定标获得,具体计算方法为:

      (1)内外黑体绝对辐射定标方程如公式(8)所示:

      式中:$\overline {D{N_i}} $$\overline {D{N_o}} $分别为内外黑体平均灰度值;KiCi分别为内黑体定标的增益、截距;KoCo分别为外黑体的定标增益、截距;Lei 、Leo为内、外定标黑体等效光谱辐亮度。

      (2)当内外黑体平均灰度值相同时,可根据公式(8)建立如公式(9)所示的关系表示为:

      由此可得出内外黑体定标转换系数R1R2,如公式(10)所示:

    • 首先计算内黑体定标系数KiCi,然后基于内外黑体定标转换系数计算外黑体定标系数KoCo,最后转换为星上绝对辐射定标系数KsCs,具体如下:

      (1)内定标系数计算公式如公式(11)所示:

      式中:KiCi分别为内定标的增益和截距;$ \overline {D{N_h}} $$ \overline {D{N_l}} $分别为内定标高、低温黑体平均灰度值;LehLel分别为内定标高、低温黑体等效光谱辐亮度。

      (2)外定标系数计算公式如公式(12)所示:

      式中:KoCo分别为外定标的增益和截距。

      (3)星上绝对辐射定标系数计算公式如公式(13)所示:

      式中:KsCs分别为星上绝对辐射定标的增益和截距。

    • (1)黑体定标数据获取

      研究选取2022年01月12日第1850轨GF5B VIMI B11~B12谱段的数据进行处理分析,图3(a)、(b)为星上下传高温黑体图像数据,图3(c)、(d)为星上下传低温黑体图像数据。研究选取一个探测元的整轨图像响应灰度值成图,如图4所示,可见每个通道中均含有一组高、低温黑体定标数据(红框处),可用于星上黑体绝对辐射定标。

      Figure 3.  Blackbody image data

      (2)相对辐射校正

      星上黑体对应各通道灰度值由星上下传的图像数据得到,采用公式(1)对图像数据进行相对辐射校正,分别选取相对辐射校正前后高低温黑体的探测元灰度值成图,如图5所示。由图可知,在相对辐射校正前灰度值波动较大,说明各探测元响应差异较大(图中蓝线);而相对辐射校正后灰度值波动较小,基本保持一致(图中红线)。相对辐射校正后高低温黑体图像数据如图6所示,通过与星上下传高低温黑体原始图像数据(图3)对比可得,相对辐射校正后各探测元响应差异明显减小。

      Figure 4.  DN of a probe on the whole orbit image

      Figure 5.  B11-B12 blackbody relative radiation correction

      Figure 6.  High and low temperature blackbody image data after relative radiation correction

      (3)高低温黑体平均灰度值提取

      高低温图像数据经过相对辐射校正后,采用公式(3)计算出成像仪各通道的平均灰度值如表1所示。

      BlackbodyAverage DN
      B11B12
      High temperature blackbody1 271.613 6831 328.266 478
      Low temperature blackbody987.581 657 01076.938 745

      Table 1.  Average DN of imager channel

      (4)高低温黑体等效光谱辐亮度计算

      首先,分别计算两个高温黑体和两个低温黑体的温度,结果如图7所示。由图可得,星上高低温黑体温度很稳定,低温黑体1的温度为(279±0.47) K,低温黑体2的温度为(279±0.55) K;高温黑体1的温度为(300±0.48) K,高温黑体2的温度为(300±0.37) K。然后,分别对高低温黑体温度进行均值化,并将其与各通道的光谱响应函数进行卷积获得高低温黑体等效光谱辐亮度,得到的成像仪各通道等效光谱辐亮度计算结果如表2所示。

      Figure 7.  High and low blackbody temperature

      BlackbodyEquivalent spectral radiance/W·m−2·sr−1·μm−1
      B11B12
      High temperature blackbody9.6302908.977463
      Low temperature blackbody6.8733486.605330

      Table 2.  Equivalent spectral radiance of imager channel

      (5)定标结果

      根据热红外星上黑体绝对辐射定标方法模型,基于成像仪各通道高低温等效光谱辐亮度,并结合各通道高低温平均灰度值,得到星上内黑体定标系数如图8所示;然后,计算成像仪外定标系数,进而转换为星上绝对辐射定标系数KsCs,如表3所示。

      Figure 8.  Calibration of on-board inner blackbody

      Calibration coefficientB11B12
      Ks0.010 4750.010 154
      Cs−3.687 025−4.552 373

      Table 3.  Calibration coefficient of imager channel

    • 根据GF5B热红外通道星上定标流程可知,星上定标系统误差如表4所示,定标误差来源具体如下:

      NumberError sourceError
      σ1Absolute calibration of ground vacuum radiation1.159%
      σ2Blackbody calibration on-board0.410%
      σ3Blackbody temperature uniformity0.310%
      σ4Blackbody stability0.027%
      Total error1.268%

      Table 4.  Accuracy analysis of on-board blackbody calibration

      (1)地面真空辐射绝对定标精度:1)外黑体辐射源:黑体辐射源为相机真空辐射定标的基准源,其中,外定标黑体的发射率为0.99±0.015,温度均匀性达±0.25 K,测温精度达±0.01 K,标定的温度不确定度为0.3 K,经计算可得外黑体辐射源的误差为0.563%;2)相机成像仪不稳定性:采用相机默认工况下一轨连续采集的DN值,将不同探测元输出信号不稳定度进行均值化,可得系统不稳定性为0.14%;3)量化误差:量化位数为12 bit,量化误差为0.05%;4)系统响应非线性:各谱段默认参数下线性度不低于0.999 3,因此系统响应非线性为0.07%;5)相机相对光谱响应度:按相对光谱相应测试设备精度,相机相对光谱响应度取1%。综上所述,真空辐射定标的总不确定度为1.159%。

      (2)星上黑体标定精度:相机使用的星上定标黑体在总装前,在计量院进行了精确标定,其标定精度由计量院出具的标定证书给出。黑体标定精度在0.23 K以内。星上黑体标定时,由温控盒进行测控温,与星上工作状态一致。将温度不确定度进行以300 K为基准的温差辐亮度折算再与300 K黑体辐亮度相比,得到温度标定不确定度为0.410%。

      (3)黑体温度均匀性:相机总体设计中,通过相机布局,保证星上黑体工作面与相机成像光学系统的出瞳尽量接近,通过分色片就到达探测器,黑体温度均匀性为0.25 K,因此星上黑体温度均匀性对在轨定标精度影响小于0.310%。

      (4)星上黑体辐射源的稳定性:影响星上黑体稳定性的主要因素是黑体控温的稳定性,星上定标黑体控温稳定性为±0.02 K/10 s。将黑体控温稳定性进行以300 K为基准的温差辐亮度折算在与以300 K黑体辐亮度相比,可得对星上定标精度的影响量为0.027%。

      式中:$ {\sigma }_{总} $为辐射定标的总误差;$ {\sigma _1} $$ {\sigma _2} $$ {\sigma _3} $$ {\sigma _4} $分别为地面真空辐射绝对定标、星上黑体标定、黑体温度均匀性、黑体稳定性的误差。

      综合上述分析,由公式(14)可得相机的星上辐射定标总误差为1.268%,折合温度为299.1 K@300 K,因此在轨后星上定标系统的绝对定标精度为0.9 K。

    • 烟台自动观测浮标采用耐腐蚀、耐撞击的聚脲弹性材料制作,聚脲标体采用不锈钢材料制作尾座和上部支架及内部龙骨,可长期在海洋环境下连续运行。浮标系统分别由浮标体与锚系、数据采集系统、传输定位系统、供电系统和传感器五部分组成,可以获取站点状态参数数据、气象数据、水文数据三类。浮标布设在各监控点后,无需人工干预,能保证监测数据实时传输、数据准确、系统可靠,是一个集智能化、模块化于一体的高性能海洋监测系统,浮标现场布设及自动观测如图9所示。其中,红外海表水温采用红外温度传感器设备测量,如图10所示,仪器的数据采集频率设定为2 s/次,在野外条件下不间断测量,测温范围为−40~70 ℃,精度为± 0.2 ℃。

      Figure 9.  Buoy deployment and automatic observation

      Figure 10.  Infrared temperature sensor

    • 研究获取2022年01月12日与GF5B卫星同步过境观测的烟台浮标数据,从中提取卫星过境时间的海表温度数据用于验证分析。卫星传感器对定标场地进行观测时接收的辐射信息包括三部分:(1)是来自水表的辐亮度;(2)是大气向上辐亮度;(3)是水表反射的大气向下辐亮度通过大气衰减到达卫星[18]。成像仪接收的单色辐亮度如公式(15)所示。为更好地进行在轨定标,卫星接收的单色辐亮度需要采用通道光谱响应函数进行卷积得到通道辐亮度。

      式中:Ls为卫星接收的单色辐亮度;Lw为水体在卫星所在方向的辐亮度;Lup为大气上行单色辐亮度;Ldown为大气下行单色辐亮度;τ为大气路径的透过率;ρ为水体比辐射率。在热红外波段,海表比辐射率随波长的变化比较平缓,用通道中心波长处的比辐射率代替。

      利用辐射传输模型MODTRAN,基于中纬度冬季大气模式,输入卫星过境时刻的海表温度、实时大气参数数据、卫星路径观测几何参数等数据,结合通道光谱响应函数,计算出同步区观测天顶角条件下的大气上下行辐射和大气透过率。将MODTRAN辐射传输模型计算的大气上下行辐射和大气透过率分别与GF5B各通道光谱响应函数进行卷积,得到卫星通道等效大气上下行辐射和大气透过率,并结合等效目标辐亮度得到成像仪各通道入瞳处的等效光谱辐亮度。

    • 2022年01月12日与烟台浮标同步观测的卫星影像如图11所示,卫星影像数据文件名称为“GF5B_VIMI_N37.3_E121.8_20220112_001850_L10000079191”,轨道号为1850轨,产品级别为一级。卫星与烟台浮标同步验证区域如图11中的红框所示。采用生产的定标系数计算同步观测区域内卫星成像仪入瞳处辐亮度,并对其进行均值化。

      Figure 11.  Satellite image and satellite-to-ground verification area

    • 采用公式(6)、(7)建立通道等效辐亮度 Li 与通道亮温Ti 的查找表,建表过程中,Ti+1Ti 取0.01 K,Ti ∈ [240,320]。基于上述地面测量监测和同步过境GF5B卫星遥感监测的各通道入瞳处等效光谱辐亮度,利用查找表得到传感器入瞳处的亮温。计算结果如表5所示,由表可知,GF5B卫星和烟台浮标计算所得的B11通道辐亮度相对差异为0.64%,B12通道辐亮度相对差异为1.35%;卫星和地面测量监测的B11通道亮温分别为273.78、273.45 K,差异为0.33 K,卫星和地面测量监测的B12通道亮温分别为272.58、273.35 K,差异为0.77 K,由此可见亮温差异均在0.8 K以内,说明两组数据具有较好的一致性。

      Data sourceRadiance/
      W·m−2·sr−1·μm−1
      Brightness temperature/K
      B11B12B11B12
      Satellite data6.225.91273.78272.58
      Yantai buoy data6.185.99273.45273.35

      Table 5.  Comparison of radiance and channel brightness temperature from different data sources

    • 文中基于GF5B卫星热红外星上定标黑体,选取2022年01月12日星上黑体定标数据,通过计算成像仪内黑体高低温等效辐亮度值和卫星通道实际响应平均灰度值得到内黑体定标系数并根据内外黑体定标转换系数,实现了成像仪热红外通道的星上绝对辐射定标。对星上定标系统进行了精度分析,并采用地面同步烟台浮标测量数据对星上黑体定标精度进行评估与验证,结果表明:相机的星上辐射定标总误差为1.268%,折合温度为299.1 K@300 K,在轨后星上定标系统的绝对定标精度为0.9 K。星地验证结果表明B11通道亮温的偏差为0.33 K,B12通道亮温的偏差为0.77 K,亮温差异均在0.8 K以内,说明GF5B卫星热红外通道在轨星上定标精度较高,结果真实可靠。

      相较于场地定标和交叉定标,采用星上黑体定标更高频、高效,但卫星在轨定标系统的灵敏度会随时间发生变化,为了更好地评估星上黑体定标精度,后续将与辐射定标场地面同步测量数据以及其他高精度定标的遥感器进行长期跟踪分析与匹配验证。该研究方法基于GF5B热红外星上定标黑体而构建,对其他卫星热红外遥感器星上黑体定标具有重要的参考价值。

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