Multi-station Fusion GNSS-IR Water Level Monitoring Based on Robust Estimation Method

SHAN Qiang; JIANG Weiping; CHEN Qusen; LIU Kai; ZHANG Mingyuan; ZOU Xiaowei

doi:10.13203/j.whugis20240117

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Multi-station Fusion GNSS-IR Water Level Monitoring Based on Robust Estimation Method

Geodesy and Survey Engineering | 更新时间：2026-11-05

- Multi-station Fusion GNSS-IR Water Level Monitoring Based on Robust Estimation Method
- Geomatics and Information Science of Wuhan University Vol. 51, Issue 5, Pages: 944-954(2026)
- 作者机构：
  
  1.武汉大学卫星导航定位技术研究中心，湖北武汉，430079
  2.湖北珞珈实验室，湖北武汉，430079
  3.常州市测绘院，江苏常州，213003
  4.常州市地理信息智能技术中心，江苏常州，213003
- 作者简介：
- 基金信息：
- DOI：10.13203/j.whugis20240117
  CLC： P228
- Received：14 January 2025，
  
  Published：05 May 2026
- 稿件说明：
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单强,姜卫平,陈渠森，等.基于稳健估计的GNSS-IR多测站融合水位监测方法[J].武汉大学学报（信息科学版）,2026,51(5):944-954.

SHAN Qiang,JIANG Weiping,CHEN Qusen,et al.Multi-station Fusion GNSS-IR Water Level Monitoring Based on Robust Estimation Method[J].Geomatics and Information Science of Wuhan University,2026,51(5):944-954.
单强,姜卫平,陈渠森，等.基于稳健估计的GNSS-IR多测站融合水位监测方法[J].武汉大学学报（信息科学版）,2026,51(5):944-954. DOI：,10.13203/j.whugis20240117

SHAN Qiang,JIANG Weiping,CHEN Qusen,et al.Multi-station Fusion GNSS-IR Water Level Monitoring Based on Robust Estimation Method[J].Geomatics and Information Science of Wuhan University,2026,51(5):944-954. DOI：,10.13203/j.whugis20240117

摘要

全球导航卫星系统（global navigation satellite system，GNSS）干涉反射（interferometric reflectometry

IR）测量技术是一种有效的“遥感水位计”，能够检索海洋、河流、湖泊、水库等在全球参考基准下的水位信息。然而，当测站观测环境复杂、接收卫星信号受限时，GNSS-IR测量技术接收的水面反射信号信噪比序列数量不足，导致单一测站水位反演精度降低。为此，提出一种基于稳健估计的GNSS-IR多测站融合水位监测方法，将面向同一水体的所有测站卫星弧段反演点联合优化定权，削弱各测站反演离群粗值的影响，提高水位监测模型的鲁棒性和稳定性。为验证所提方法的有效性，利用中国山西省西龙池抽水蓄能电站上水库3个接收不同区域水面反射信号的监测站数据开展实验。结果表明，在面对抽水蓄能电站日变幅达18.7 m的水位快速升降过程时，融合水位反演结果与水位计实测数据相关系数高达0.983，且多测站融合水位结果精度显著优于单测站水位监测，融合反演结果的相对精度为0.06，较单个测站监测结果提高了30%~70%。

Abstract

Objectives

As an effective “remote sensing water level gauge”

the global navigation satellite system (GNSS) -interferometric reflectometry (IR) technique

with its advantages of wide coverage

high precision and strong anti-interference ability

has become an important means for retrieving water level information in oceans

rivers

lakes

and reservoirs against the global reference frame. However

in practical applications

when the observation environment of the station is complicated and the capacity of receiving satellite signals is limited

the number and length of the signal-to-noise ratio (SNR) sequences of the water surface reflections are insufficient

which reduces the inversion accuracy of GNSS-IR water level monitoring. Especially when dealing with special scenarios such as rivers with a narrow reflection area on the water surface

or pumped storage power stations with significant daily fluctuations in water level

a single GNSS station often encounters problems such as insufficient number and limited length of the SNR sequences of the reflected water surface signals

making it difficult to comprehensively reflect the characteristics of water level changes.

Methods

Therefore

We propose a GNSS-IR multi-station fusion water level monitoring method based on robust estimation. This method fully utilizes the redundant observational data from multiple measurement stations in the same water area by IGGⅢ equivalent weight function and reduces the influence of outlier rough values of all stations by optimizing the inversion points of satellite arcs of all stations.

Results

To verify the effectiveness of the proposed method

experiments are conducted using data from three monitoring stations in the upper reservoir of the Xilongchi pumped storage power station

each receiving reflected signals from different water surface areas. Actual water level gauge measurements at a 1 h sampling rate are collected and converted to the WGS-84 reference frame for comparison. The results show that

for the sudden water level fluctuation process with a daily variation of 18.7 m

the correlation coefficient between the fused inversion results and the gauge measurements reaches as high as 0.983. The standard deviation between the multi-station fusion results and the measured data is 1.13 m

with a relative accuracy of 0.06. Compared with single-station inversion results

the accuracy of the proposed fusion method improves by 30% to 70%

effectively compensating for the insufficient inversion points observed in single-station results during certain periods.

Conclusions

It is demonstrated that the proposed method significantly enhances the performance of GNSS-IR water level monitoring in scenarios with insufficient single-station data

while significantly improving the robustness and stability of the water level monitoring model. The research results provide crucial technical support for advancing the application of GNSS-IR technology to a broader spectrum of remote sensing fields

facilitating its practical deployment in complex hydrological monitoring scenarios.

关键词

Keywords

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