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高斯拟合与滑动窗口相结合的GNSS-R海平面测高方法

王井利 周秀一 李如仁 王继野

辽宁工程技术大学学报(自然科学版)2023,Vol.42Issue(5):555-563,9.
辽宁工程技术大学学报(自然科学版)2023,Vol.42Issue(5):555-563,9.DOI:10.11956/j.issn.1008-0562.2023.05.006

高斯拟合与滑动窗口相结合的GNSS-R海平面测高方法

GNSS-R sea level altimetry method based on Gaussian fitting and sliding window

王井利 1周秀一 1李如仁 1王继野2

作者信息

  • 1. 沈阳建筑大学 交通工程学院,辽宁 沈阳 110168
  • 2. 中铁十九局集团 矿业投资有限公司,北京 100161
  • 折叠

摘要

Abstract

In order to improve the problem of poor signal separation and large deviation in the process of sea level height inversion,this paper proposes a new method of sea level height inversion based on Gaussian multi-peak fitting + sliding window,which can obtain high-quality signal-to-noise ratio sequence.The SNR(signal to noise ratio)of BDS(Beidou Navigation Satellite System)satellite B2,B6 and B7 bands at MAYG station was selected to invert the sea level height by Gaussian multi-peak fitting + sliding window method,and the inversion results of polynomial and wavelet filtering methods and tide station data were compared and verified.The results show that the accuracy of Gaussian fitting inversion results is 29%and 19%higher than that of polynomial and wavelet filtering methods,respectively,and the correlation is better.After combining the sliding window,the effective point of the inversion result is increased to 4.5 times before the windowing,and the time resolution is greatly improved.Compared with the single-frequency data inversion results,the effective point of the joint multi-frequency data inversion results is increased by more than 3 times,and the resolution is further improved while ensuring the accuracy.The results show that the GNSS-R(global navigation satellite system-reflectometry)sea level height inversion method combining Gaussian fitting and sliding window can better reflect the sea level height.

关键词

GNSS-R/高斯拟合/信噪比/海平面高度/滑动窗口

Key words

GNSS-R/Gaussian fitting/signal to noise ratio/sea level height/sliding window

分类

天文与地球科学

引用本文复制引用

王井利,周秀一,李如仁,王继野..高斯拟合与滑动窗口相结合的GNSS-R海平面测高方法[J].辽宁工程技术大学学报(自然科学版),2023,42(5):555-563,9.

基金项目

国家自然科学基金项目(51774204) (51774204)

辽宁工程技术大学学报(自然科学版)

OA北大核心CSTPCD

1008-0562

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