The Doppler scatterometer is a type of rotating radar platform used for the estimation and monitoring of ocean current to achieve fast mapping of global vector current with a monostatic system. Accurate measurement of the ocean surface current imposes strong requirements on the accuracy of the platform errors. If the ocean surface current speed measurement accuracy can be less than 5 cm/s, the slant range error should be smaller than 20 m and the attitude measurement error should reach 1 × 10−3°. No available attitude determination technique is capable of this level of accuracy. In this study, we propose a method of platform errors estimation based on echo signals. A model describing the relation of the Doppler centroid to platform errors is established. Then, a Doppler centroid frequency estimation method based on deramping is proposed to improve the estimation accuracy, which showed a 26.15% improvement compared with the classical average cross-correlation coefficient method. Finally, using the weighted least square technique, the platform errors estimation method based on Doppler centroid estimation of echo signals from the stationary land area is constructed. Simulation experiments were performed to analyze the accuracy, feasibility, and robustness of the proposed method. Through simulation of one circle echo data, the root-mean-square errors of slant range error, roll, pitch, and yaw were shown to reach 1.12 × 10−1 m, 1.69 × 10−6°, 2.44 × 10−6°, and 8.52 × 10-7°, respectively. These findings represent a much smaller error level than the requirement for the slant range error and attitude angles.


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    Title :

    A Platform Errors Estimation Method Based on Radar Echo for Spaceborne Doppler Scatterometer


    Contributors:
    Yao, Xiaonan (author) / Wang, Xiaoqing (author) / Liu, Lixia (author) / Liu, Shubo (author) / Su, Xiang (author) / Huang, Haifeng (author)


    Publication date :

    2023-10-01


    Size :

    3569207 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English