Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2305.06735

Unsupervised noise reductions for gravitational reference sensors or accelerometers based on Noise2Noise method

Zhilan Yang·Haoyue Zhang·Peng Xu·Ziren Luo
View original source ↗Read source document ↗Export metadata ↓

Abstract

Onboard electrostatic suspension inertial sensors are important applications for gravity satellites and space gravitational wave detection missions, and it is important to suppress noise in the measurement signal. Due to the complex coupling between the working space environment and the satellite platform, the process of noise generation is extremely complex, and traditional noise modeling and subtraction methods have certain limitations. With the development of deep learning, applying it to high-precision inertial sensors to improve the signal-to-noise ratio is a practically meaningful task. Since there is a single noise sample and unknown true value in the measured data in orbit, odd-even sub-samplers and periodic sub-samplers are designed to process general signals and periodic signals, and adds reconstruction layers consisting of fully connected layers to the model. Experimental analysis and comparison are conducted based on simulation data, GRACE-FO acceleration data and Taiji-1 acceleration data. The results show that the deep learning method is superior to traditional data smoothing processing sol

Explore related subjects

physics.geo-phastro-ph.IMphysics.ins-det

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhilan Yang, Haoyue Zhang, Peng Xu, Ziren Luo. 2023-05-11. Unsupervised noise reductions for gravitational reference sensors or accelerometers based on Noise2Noise method. https://arxiv.org/abs/2305.06735

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Assessing foundational atomistic models for iron alloys under Earth's core conditions

We assess the capability of recently developed foundational atomistic models (FAMs) to simulate iron alloys under the extreme pressures and temperatures of Earth's core. Static equations of state for hexagonal close-packed (hcp) and body-centered cubic (bcc) iron, computed using 17 FAMs, are benchmarked against ab initio calculations. Two representative models, MatterSim and MACE, are further evaluated for their ability to reproduce phonon spectra, liquid structure, and melting relations of iron at core conditions. While both models capture several key properties, MACE substantially overestimates the stability of bcc iron and fails to correctly describe the stability of hcp iron. Their performance is also examined for binary liquids, superionic phases, and a seven-component Fe-Ni-Si-S-O-H-C liquid. Although these FAMs were not explicitly trained on data from core conditions, they can reproduce several structural and dynamical properties across a wide range of compositions. However, none of the tested models consistently reproduces all first-principles benchmarks. By analyzing the origins of these discrepancies, we identify several limitations of current FAMs, particularly the lack of an explicit treatment of thermal electronic excitations, which significantly affect phase stability and thermodynamic properties under core conditions. We further discuss directions for improving FAMs to enable predictive simulations of core-forming materials under extreme conditions.

physics.geo-ph↗
arXiv2026

Time-Resolved Surface-Fault Displacement During the 2026 Kumamoto Earthquake From Near-Fault Video

Video recordings can reveal how rapidly fault displacement develops at the Earth's surface, but camera motion and recording artifacts can obscure the ground signal. We analyze a secondary copy of security-camera footage that captured surface displacement during the 28 July 2026 Kumamoto earthquake; the native recording was unavailable and could not be recovered. Two independent image-tracking methods were used. Optical flow follows identifiable image features, whereas normalized cross-correlation (NCC) template matching follows fixed image patches by their similarity. Both measured target-region motion relative to spatially separated reference regions while correcting motion shared by the recording. Image displacement was calibrated to the magnitude of the field-measured offset vector: 1.05 m right-lateral and 0.90 m east-side-up, or 1.383 m in total. We characterize the principal rise by the time required for displacement to progress from 20% to 80% of the selected final level. Across prespecified endpoint choices, optical flow gives 0.866-0.901 s and NCC gives 0.910-0.928 s. These durations correspond to average rates of 0.920-0.958 and 0.895-0.912 m/s, respectively. Checks using independently published tracking windows reproduce the displacement scale, although exact timing is more sensitive in spatially restricted tests. The record also shows an early apparent peak and decline followed by renewed apparent horizontal displacement. Because that later motion may represent either continued ground displacement or the geometry of the secondary recording, neither the permanent endpoint nor physical overshoot can be determined. The most robust conclusion is that the central part of the surface displacement developed in approximately 0.9 s at an average rate near 0.9 m/s.

physics.geo-ph↗
arXiv2026

Shape matters: DEM investigation of geometry-controlled mechanical response in irregular rock fragments under static and dynamic loading

Mechanical characterization of subsurface rock formations typically requires standardized cylindrical core specimens, which are often unavailable from fractured or unconventional reservoir sequences. This study uses a Discrete Element Method (DEM) framework calibrated to Sulphur Mountain Formation siltstone to investigate how fragment geometry governs mechanical response in irregular rock particles, which are direct analogues of drill cuttings. Nineteen specimens (18 procedurally generated irregular geometries and one reference Brazilian disk), normalized to a 10 mm bounding sphere radius, were tested under quasi-static (Brazilian-type) and dynamic (Short Impact Load Cell) loading modes. Four mechanical outputs of failure force (Ff), apparent strength (σf), apparent stiffness (Ka), and stiffness (E) were regressed against seven retained shape descriptors. Results show that force-based quantities are strongly controlled by the surface-area-to-volume (SA/V) ratio under static loading (Adj. R2 = 0.69), while area-normalized quantities (σf and E) are geometrically insensitive. Dynamic loading amplifies geometric sensitivity for failure force and introduces an independent role for surface concavity depth. These findings establish a preliminary quantitative framework for interpreting mechanical measurements from irregular rock fragments when a standardized core is unavailable.

physics.geo-ph↗