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Snow depth retrieval using GPS signal-to-noise ratio data based on improved complete ensemble empirical mode decomposition
Snow is essential to the Earth's water source and plays a significant role in studying the climate system and hydrological cycle. Snow depth...
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Analysis of signal-to-noise ratio retrieved from multi-GNSS satellite data of land surface reflections
The reflection of Global Navigation Satellite System (GNSS) signals, known as GNSS reflectometry (GNSS-R), has made significant progress in...
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Application of Low Signal-To-Noise Ratio Seismic Data Processing Technology in the Northern Margin of Qinshui Basin
In the northern margin of Qinshui Basin, the topographic relief is sharp, near surface lithology is complicated, and the thickness of loess is...
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Machine learning-based snow depth retrieval using GNSS signal-to-noise ratio data
GNSS-IR enables the extraction of environmental parameters such as snow depth by analyzing signal-to-noise ratio, indicating the strength of the GNSS...
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Performance assessment of GNSS-IR altimetry using signal-to-noise ratio data from a Huawei P30 smartphone
Global Navigation Satellite System interferometric reflectometry (GNSS-IR) is a technique that utilizes multipath effects to sense the near-surface...
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Reduced Southern Ocean warming enhances global skill and signal-to-noise in an eddy-resolving decadal prediction system
The impact of increased model horizontal resolution on climate prediction performance is examined by comparing results from low-resolution (LR) and...
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Missing eddy feedback may explain weak signal-to-noise ratios in climate predictions
The signal-to-noise paradox that climate models are better at predicting the real world than their own ensemble forecast members highlights a serious...
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An improved method of local mean decomposition with adaptive noise and its application to microseismic signal processing in rock engineering
The processing and interpretation of microseismic (MS) signals are the basis for obtaining source information of MS events in rock engineering....
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Understanding the signal-to-noise paradox in decadal climate predictability from CMIP5 and an eddying global coupled model
Recent research suggests the widespread existence of the signal-to-noise paradox in seasonal-to-decadal climate predictions. The essence of the...
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Detection of synchronous spoofing on a GNSS receiver using weighed double ratio metrics
Spoofing signal detection is an essential process in GNSS anti-spoofing. The detection probability of the existing metrics degrades significantly for...
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Calculation method of the signal-to-noise ratio attribute of seismic data based on structural orientation
At present, most signal-to-noise ratio (SNR) estimation methods can only calculate the global and not the local SNR of seismic data. This paper...
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Denoising of Seismoelectric Logging Signal Based on Stochastic Resonance
Seismoelectric well logging is a new geophysical logging technique based on acoustic and electric conversion of double electric layers in porous...
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Influence of flooding on GPS carrier-to-noise ratio and water content variation analysis: a case study in Zhengzhou, China
Based on the Global Positioning System interferometric reflectometry (GPS-IR), the influence of flood on GPS carrier-to-noise ratio (CNR) and water...
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Damage quantification in beam-type structures using modal curvature ratio
Modal curvature ratio approach for the localization and quantification of damage in beam-type structures is proposed, demonstrating capability across...
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First-arrival automatic picking based on improved energy ratio method and outlier detection theory
Based on the energy ratio method, an automatic picking method with strong noise resistance is proposed. It considers the influence of the current...
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Microseismic Signal Denoising Based on Variational Mode Decomposition With Adaptive Non-local Means Filtering
Microseismic signals are characterized by a low signal-to-noise ratio and a high degree of non-stationary noise. Therefore, attenuation of noise in...
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A two-stage seismic data denoising network based on deep learning
Seismic data with a high signal-to-noise ratio is beneficial in the inversion and interpretation. Thus, denoising is an indispensable step in the...
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Efficiency of post-stack processing in enhancing seismic data quality: a case study of Southwest Qarun-Field, Gindi Basin, Egypt
In a broad sense, seismic data quality depends on the signal-to-noise ratio ( S / N ). Increasing the S / N ratio when acquiring seismic data in the field...
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Seismic noise attenuation using post-stack processing: a case study of Rabeh East Oil Field, Gulf of Suez Basin, Egypt
Seismic data are usually contaminated with random and coherent noise. This noise prevents the accurate imaging of seismic sections and lead to...
