IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2023)

Improving GNSS-R Ocean Wind Speed Retrieval for the BF-1 Mission Using Satellite Platform Attitude Measurements

  • Chenxin Chen,
  • Xiaoyu Wang,
  • Zhao Bian,
  • Haoyun Wei,
  • Dongdong Fan,
  • Zhaoguang Bai

DOI
https://doi.org/10.1109/JSTARS.2023.3243206
Journal volume & issue
Vol. 16
pp. 2121 – 2133

Abstract

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The receive antenna gain is needed to accurately calibrate the normalized bistatistic radar cross section measured by the BF-1 mission, which is a global navigation satellite system reflectometry (GNSS-R) constellation of two microsatellites and the first Chinese GNSS-R satellite mission. The instability of the satellite platform is the main cause of receive antenna gain errors. To obtain a high precision gain value, a calibration method that remaps the ocean surface detection location to the receive antenna pattern using satellite platform attitude measurements is proposed in this article. Thirty-two orbits of delay Doppler maps data, which were greatly disturbed by the attitude, are selected to test the effectiveness of the proposed algorithm. The accuracy of wind speed retrieval is analyzed, and results show that the data calibration algorithm is effective in reducing the wind speed retrieval error. Compared with the un-calibrated data, the data subjected to the calibration algorithm show a significant improvement of 19.33% in correlation coefficient and average decreases of 30.91% and 42.57% in root-mean-square error and mean bias error, respectively. Moreover, the comparison highlights that the influence of the satellite platform attitude disturbance on wind speed retrieval is abated significantly. The proposed approach can effectively improve the quality of GNSS-R measurements, allowing for a better understanding of global weather abnormalities and generally improving weather forecasting.

Keywords