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    井成等:Retrieval of sea surface winds under hurricane conditions from GNSS-R observations

    作者:来源:发布时间:2016-10-14
     Retrieval of sea surface winds under hurricane conditions from GNSS-R observations
    作者:Jing, C (Jing Cheng)[ 1 ] ; Yang, XF (Yang Xiaofeng)[ 1 ] ; Ma, WT (Ma Wentao)[ 1 ] ; Yu, Y (Yu Yang)[ 1 ] ; Dong, D (Dong Di)[ 1 ] ; Li, ZW (Li Ziwei)[ 1 ] ; Xu, C (Xu Cong)[ 2 ]
    ACTA OCEANOLOGICA SINICA
    卷: 35  期: 9  页: 91-97
    DOI: 10.1007/s13131-016-0933-7
    出版年: SEP 2016
    摘要
    Reflected signals from global navigation satellite systems (GNSSs) have been widely acknowledged as an important remote sensing tool for retrieving sea surface wind speeds. The power of GNSS reflectometry (GNSS-R) signals can be mapped in delay chips and Doppler frequency space to generate delay Doppler power maps (DDMs), whose characteristics are related to sea surface roughness and can be used to retrieve wind speeds. However, the bistatic radar cross section (BRCS), which is strongly related to the sea surface roughness, is extensively used in radar. Therefore, a bistatic radar cross section (BRCS) map with a modified BRCS equation in a GNSS-R application is introduced. On the BRCS map, three observables are proposed to represent the sea surface roughness to establish a relationship with the sea surface wind speed. Airborne Hurricane Dennis (2005) GNSS-R data are then used. More than 16 000 BRCS maps are generated to establish GMFs of the three observables. Finally, the proposed model and classic one-dimensional delay waveform (DW) matching methods are compared, and the proposed model demonstrates a better performance for the high wind speed retrievals.
    通讯作者地址: Yang, XF (通讯作者)
    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
    地址:
    [ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
    [ 2 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Natl Engn Ctr Geoinformat, Beijing 100101, Peoples R China
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