Results 51 to 60 of about 879 (182)
Laser &Photonics Reviews, Volume 20, Issue 14, 22 July 2026.This work demonstrates a high‐fidelity stability transfer from an optical reference to a high‐repetition‐rate microcomb using a mode‐locked laser bridge. By employing electro‐optic sampling timing detection, femtosecond‐level synchronization and 10−18‐level fractional frequency stability are achieved.
Changmin Ahn +4 more
wiley +1 more source
Effects of Surface Errors of Antennas on Detection Performance of Space VLBI
Aerospace, 2022 This work investigates the effects of the surface errors of the satellite antenna on the detection performance of the space VLBI system. First, the relationship between the surface errors and the antenna gain loss is analyzed, and then the influence of ...
Yangyang Zhang, Huijie Liu, Xingfu Liu
doaj +1 more source
The AuScope geodetic VLBI array [PDF]
Journal of Geodesy, 2013 Journal of Geodesy, March ...
Lovell, J. +17 more
openaire +3 more sources
MSWD: A Hybrid Machine‐Learning Framework for Slant Wet Delay Modeling
Journal of Geophysical Research: Atmospheres, Volume 131, Issue 12, 28 June 2026.Abstract Space geodetic techniques such as Global Navigation Satellite Systems (GNSS) and Very Long Baseline Interferometry (VLBI) are limited by direction‐dependent tropospheric delays, with slant wet delay (SWD) being the most variable component and a major error source.
Zhenyi Zhang, Benedikt Soja
wiley +1 more source
РАДИОСТРУКТУРА ИСТОЧНИКА 1803÷784
Odessa Astronomical Publications, 2011 Results of processing of data of ground-space VLBI experiment titled V053 are presented. These observations were made in 1997 October with 10 antennas of American interferometer VLBA and with Japan space telescope VSOP (VLBI Space Orbit Program).
A. А. Чуприков
doaj +1 more source
International Astronomical Union Colloquium, 1990 AbstractVLBI observations using a satellite in earth orbit and ground antennas in Japan and Australia were conducted in 1986, 1987, and 1988. Sources were detected on space-ground baselines at both observing frequencies: 2.3 and 15 GHz. The coherence on space-ground baselines for 340 s was 90% at 2.3 GHz and 76% at 15 GHz.
openaire +1 more source
Describing the uncertainties in VLBI images [PDF]
Proceedings of 11th European VLBI Network Symposium & Users Meeting — PoS(11th EVN Symposium), 2016 We are investigating a new approach to modelling uncertainties in individual pixels of Very Long Baseline Interferometry (VLBI) intensity (Stokes I, Q, U) images. Comparison of distributions of our calculated uncertainties for model sources with the results of Monte Carlo simulations shows that our method correctly reproduces the overall level and ...
Coughlan, Colm P., Gabuzda, Denise C.
openaire +2 more sources
Ionospheric Data Fusion With GNSS, GNSS‐RO and Satellite Altimetry Based on Machine Learning
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 3, June 2026.Abstract Global Ionospheric Maps (GIMs) are essential in Global Navigation Satellite System (GNSS) applications, particularly for correcting ionospheric delays in single‐frequency positioning. GIMs are mainly derived from dual‐frequency GNSS observations, but the uneven distribution of ground stations—sparse over oceans—reduces accuracy in these ...
Marcel Iten, Shuyin Mao, Benedikt Soja
wiley +1 more source
Radio Science, Volume 61, Issue 6, June 2026.Abstract Since its observation in 2019, the first image of a super‐massive black hole using Very Long Baseline Interferometry (VLBI) with an Earth‐scale baseline has generated much scientific and public interest. Work is now underway to extend the baseline into space to obtain higher image resolution.
E. A. Burt +5 more
wiley +1 more source
Earth and Space Science, Volume 13, Issue 5, May 2026.Abstract Polar motion prediction is an important means to study the dynamics of Earth's rotation and detect the internal structure of the Earth. This paper proposes an LS + iTransformer method that combines the least squares (LS) method with the iTransformer deep learning model. Using IERS EOP 20 C04 data from 2000 to 2022, Fast Fourier Transform (FFT)
Huizhong Zhu +5 more
wiley +1 more source