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Radiometer calibration of airborne L-band active and passive microwave detector

  • role： First author第一作者
  • Affiliation：

    Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China

  • Email：zlinhwj@126.com
  • Introduction：孙彦龙，1988年生,男,工程师, 研究方向为微波遥感。E-mail: zlinhwj@126.com
SUN Yanlong1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

ZHAO Tianjie2,  
  • Affiliation：

    Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China

LI Enchen1,  
  • Affiliation：

    Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China

LUAN Yinghong1,  
  • Affiliation：

    Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China

WAN Guoyu1,  
  • Affiliation：

    Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China

XU Hongxin1,  
  • Affiliation：

    Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China

ZHAO Feng1,  
  • Affiliation：

    Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China

YAO Chongbin1,  
  • Affiliation：

    Shanghai Academy of Spaceflight Technology, Shanghai 201109, China

LYU Liqing3,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

Hu Lu2,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

GENG Deyuan2

resumen

The remote sensing experiment is an important way to verify the principle of remote sensing, develop remote sensing models and retrieval algorithms, and to validate remote sensing products. It is also important to promote the demonstration of satellite missions and the application of its observations in earth system science. In the ShanDian River comprehensive remote sensing experiment, a large-scale aerial remote sensing experiment with soil moisture as the primary target was carried out using the airborne L-band active and passive microwave sounder. The passive detection part, the microwave radiometer, uses a microstrip antenna, supplemented by a mechanical scanning method for multi-angle imaging observation. In order to effectively support the development of remote sensing models and algorithms, real-time calibration of brightness temperature must be performed. This paper introduces a distributed calibration method combining internal and external calibration.Due to the limitation of the space and weight of the aircraft, the end-to-end calibration method cannot be used to calibrate the system. Therefore, the step-by-step calibration method is used in the test. First use Standard noise generator on the ground to calibrate the brightness temperature of the internal noise source, and then measure the antenna radiation efficiency, main beam efficiency, cable loss and other parameters. During the flight, use the reference load and the internal noise source as the two-point standard sources. The relationship between the receiver and the input brightness temperature is obtained, and finally the parameters of the ground measurement system are substituted to obtain the calibration equation of the airborne radiometer. During the flight, the water body in the Hulunnao’er was selected as the reference point for external calibration target to correct the equation.The results show that the airborne radiation brightness temperature is relatively consistent with the ground reference point (grassland) simulated brightness temperature. The comparison shows that the minimum root mean square error is 0.93 K (September 26, 2018, H polarization), and the unbiased average The minimum square root error is 0.96K (September 24, 2018, V polarization), which effectively supports the demonstration of the domestic-made L-band microwave radiometer satellite program and the subsequent development of related research work such as quantitative inversion and downscaling.The calibration method adopted in this paper can accurately describe the complex relationship between the radiometer electrical signal and the brightness temperature. However, this study did not consider the effects of antenna port matching, aircraft pod loss, antenna pattern error, etc. During the calibration of internal noise sources on the ground, the impact of the environment and the system nonlinearity were not considered. It is necessary to take these factors into consideration in subsequent research, and the calibration accuracy can be further improved.

palabra clave

remote sensing;active and passive microwave detector;airborne remote sensing experiment;airborne microwave radiometer;calibration

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