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基于相关功率修正的地基GNSS-R土壤湿度反演
引用本文:洪学宝,张波,阮宏梁,汉牟田,杨东凯,宋曙辉.基于相关功率修正的地基GNSS-R土壤湿度反演[J].北京航空航天大学学报,2021,47(8):1558-1564.
作者姓名:洪学宝  张波  阮宏梁  汉牟田  杨东凯  宋曙辉
作者单位:1.北京航空航天大学 电子信息工程学院, 北京 100083
基金项目:浙江省基础公益研究计划LGN19D040001地理信息工程国家重点实验室开放基金课题SKLGIE2018-M-2-2
摘    要:利用全球导航卫星系统反射信号测量技术(GNSS-R)进行土壤湿度反演过程中,实际接收天线方向性会造成GNSS直反信号相关功率测量偏差。针对地基观测场景下天线方向性造成的相关功率的类余弦振荡问题,提出了基于多项式拟合的信号相关功率修正方法。为了验证所提方法的有效性,开展了地基GNSS-R土壤湿度观测实验,结果表明:基于多项式拟合的相关功率修正可以消除信号相关功率的类余弦振荡,提升GNSS-R土壤湿度反演中的观测数据有效性和反演结果准确性。 

关 键 词:全球导航卫星系统反射信号测量技术(GNSS-R)    相关功率    振荡偏差    多项式拟合    土壤湿度
收稿时间:2020-04-21

Ground-based GNSS-R soil moisture retrieval based on correlation power correction
HONG Xuebao,ZHANG Bo,RUAN Hongliang,HAN Mutian,YANG Dongkai,SONG Shuhui.Ground-based GNSS-R soil moisture retrieval based on correlation power correction[J].Journal of Beijing University of Aeronautics and Astronautics,2021,47(8):1558-1564.
Authors:HONG Xuebao  ZHANG Bo  RUAN Hongliang  HAN Mutian  YANG Dongkai  SONG Shuhui
Institution:1.School of Electronics and Information Engineering, Beihang University, Beijing 100083, China2.Jinyi Network Economy College, Jinhua Polytechnic, Jinhua 321000, China3.Beijing Vegetable Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
Abstract:In soil moisture observation using Global Navigation Satellite System Reflectometry (GNSS-R) technique, actual antennas' directionalities will bring about the biases in the correlation power measurements of the direct and reflected GNSS signals. For eliminating the cosine-like oscillatory bias of the correlation power caused by antenna directionality in ground-based scenario, this paper proposes a correlation power correction method based on the polynomial fitting. In order to verify the validity of this method, the ground-based GNSS-R soil moisture observation experiment is carried out. The experimental results show that the correlation power correction using polynomial fitting can remove the cosine-like oscillation of the correlation power waveform, and then improve the efficiency of measurement data and the accuracy of retrieval results. 
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