Sea Surface Height Estimation by Ground-Based BDS GEO Satellite Reflectometry

Wu, Jianming; Chen, Yanling; Gao, Fan; Guo, Peng; Wang, Xiaoya; Niu, Xufeng; Wu, Mengjie; Fu, Naifeng

doi:10.1109/jstars.2020.3024743

Cited by 18 publications

(6 citation statements)

References 34 publications

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“…These fixed biases are easy to correct as systematic errors. In fact, there have been some works to focus on the altimetry based on GEO satellites, such as BeiDou GEO satellite [50], communication satellite [51] and Digital Video Broadcasting satellite [52].…”

Section: Discussionmentioning

confidence: 99%

An Unbiased Multiparameter Algorithm of Retrieving Sea Surface Height Using Coastal GNSS Reflectometry

Wang¹,

Xu²,

Yang³

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Section: Discussionmentioning

confidence: 99%

An Unbiased Multiparameter Algorithm of Retrieving Sea Surface Height Using Coastal GNSS Reflectometry

Wang¹,

Xu²,

Yang³

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Nearly, 11.01% of the total data are eliminated in (2), and 3.08% of the total data are eliminated in (3). The remained dataset is divided into 80% and 20% for training and test datasets, respectively.…”

Section: Data Quality Controlmentioning

confidence: 99%

Sea Surface Wind Speed Retrieval Based on Empirical Orthogonal Function Analysis Using 2019–2020 CYGNSS Data

Chen

Guo

et al. 2022

IEEE Trans. Geosci. Remote Sensing

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This article proposes a new sea surface wind speed (SSWS) retrieval modeling algorithm based on the empirical orthogonal function (EOF) analysis for observations acquired by the global navigation satellite system reflectometry (GNSS-R). As a nonparametric modeling algorithm, it is simpler compared with the nonlinear methods. The influence of wind speed and incident angle on the modeling error is analyzed for the first time using a spectrum analysis. Three types of data from 80% CYGNSS 2019-2020 observations [delay Doppler map average (DDMA) and leading edge slope (LES)], signal incident angle, and the European Centre for Medium-Range Weather Forecasts Reanalysis V5 (ERA5) reference wind speed are used in the EOF analysis to establish two retrieval models. The remaining 20% of the data are used for accuracy evaluation after getting the final wind speed by the minimum variance (MV) estimator. As a result, when using three 0-20-m/s wind speeds of ERA5, Advanced Scatterometer (ASCAT), and the Modern-Era Retrospective Analysis for Research and Applications V2 (MERRA2) as contrasts, the root mean squared errors (RMSEs) are 1.51, 1.45, and 1.43 m/s, respectively. Compared with CYGNSS wind product, the performance of this algorithm is closer to the L2 Climate Data Record (CDR) V1.1 product than V1.0. The results demonstrate that the EOF algorithm has a good performance in retrieving SSWS and can better retain the influence of the incident angle on the observations.

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“…Global navigation satellite system (GNSS) reflectometry (GNSS-R), which was first envisioned in 1993 [1], has been proved to be an effective remote sensing tool to support emerging remote sensing applications, such as monitoring water levels [2][3][4][5][6], snow thickness [7][8][9], sea ice condition [10,11], sea waves and breeze [12][13][14][15], and soil moisture [16][17][18], etc. GNSS-R altimetry uses direct and reflected GNSS signals to address the issue of sealevel monitoring, tidal warning, and reservoir level monitoring, etc.…”

Section: Introductionmentioning

confidence: 99%

“…This abundance of single-frequency observations can alleviate the challenge of integer ambiguity resolution for low-cost devices, while the hybrid constellation can provide unique contributions to position dilution of recision (PDOP). It is expected that the increased number of satellites and improved PDOP could significantly enhance the performance of GNSS-R [3,5,34]. In this study, we configured a set of low-cost BeiDou Navigation Satellite System Reflectometry (BDS-R) devices and conducted experimental assessments of land and water surface altimetry based on single-frequency (B1I) signals.…”

Section: Introductionmentioning

confidence: 99%

Low-Cost BDS Reflectometry for Real-Time Water Surface Retrieval

Deng

Zhou

et al. 2023

Remote Sensing

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The official launch of the Chinese BeiDou Navigation Satellite System with global coverage (BDS-3) presents significant opportunities for various applications, including precision agriculture and autonomous driving, among others. With its global spatial coverage and hybrid space constellation comprising geosynchronous Earth orbit (GEO), inclined geosynchronous orbit (IGSO), and medium Earth orbit (MEO) satellites, BDS can significantly contribute to various GNSS remote sensing applications that require real-time, precise water surface height measurements with high temporal and spatial resolution, such as in tidal monitoring. In this paper, we propose a carrier-phase-based method for BDS Reflectometry (BDS-R) to precisely retrieve real-time water surface height. Firstly, the BDS-R altimetry method is introduced, along with a detailed explanation of the data processing procedures. Secondly, a quality control method tailored to the characteristics of low-cost BDS devices is developed. Thirdly, a land altimetry experiment is conducted to evaluate the precision of BDS-R and analyze the specific contribution of the BDS hybrid constellation. Finally, a water surface altimetry experiment validates the real-time monitoring capabilities for low-cost BDS-R. The results indicate that low-cost BDS-R can achieve real-time centimeter-level water level monitoring with a temporal resolution of 1 s in lakefront environments. The performance of BDS-R can be significantly improved by the BDS hybrid constellation, particularly IGSOs. It is concluded that low-cost BDS-R has great potential for promoting ground-based GNSS remote sensing applications.

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Sea Surface Height Estimation by Ground-Based BDS GEO Satellite Reflectometry

Cited by 18 publications

References 34 publications

An Unbiased Multiparameter Algorithm of Retrieving Sea Surface Height Using Coastal GNSS Reflectometry

An Unbiased Multiparameter Algorithm of Retrieving Sea Surface Height Using Coastal GNSS Reflectometry

Sea Surface Wind Speed Retrieval Based on Empirical Orthogonal Function Analysis Using 2019–2020 CYGNSS Data

Low-Cost BDS Reflectometry for Real-Time Water Surface Retrieval

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