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Multipath and non-line-of-sight (NLOS) signals are the major causes of poor accuracy of a global navigation satellite system (GNSS) in urban areas. Despite the wide usage of the GNSS in populated urban areas, it is difficult to suggest a generalized method because multipath errors are user-specific errors that cannot be eliminated by the DGNSS or a real-time kinematic technique. This paper introduces a real-time multipath estimation and mitigation technique, which considers compensation for the time offset between constellations. It also presents a mode-switching algorithm between the DGNSS and multipath mitigating mode and shows that this technique can be effectively utilized for automobiles in a deep urban environment without any help from sensors other than GNSS. The availability is improved from 64% to 100% and the error RMS is reduced from 11.1 m to 1.2 m on Teheran-ro, Seoul, Korea. Because this method does not require prior information or additional sensor implementation for high-positioning performance in deep urban areas, it is expected to gain wide usage in not only the automotive industry but also future intelligent transportation systems.

We present the first very-long-baseline interferometric (VLBI) observations of the blazar OJ287 carried out jointly with the Global Millimeter VLBI Array (GMVA) and the phased Atacama Large Millimeter/submillimeter Array (ALMA) at 3.5 mm on April 2, 2017. Participation of phased-ALMA not only has improved the GMVA north-south resolution by a factor of ~3, but also has enabled fringe detection with signal-to-noise ratios up to 300 at baselines longer than 2 G{\lambda}. The high sensitivity has motivated us to image the data with the newly developed regularized maximum likelihood imaging methods, revealing the innermost jet structure with unprecedentedly high angular resolution. Our images reveal a compact and twisted jet extending along the northwest direction with two bends within the inner 200 {\mu}as that resembles a precessing jet in projection. The component at the southeastern end shows a compact morphology and high brightness temperature, and is identified as the VLBI core. An extended jet feature that lies at ~200 {\mu}as northwest of the core shows a conical shape in both total and linearly polarized intensity, and a bimodal distribution of the linear polarization electric vector position angle. We discuss the nature of this feature by comparing our observations with models and simulations of oblique and recollimation shocks with various magnetic field configurations. Our high-fidelity images also enabled us to search for possible jet features from the secondary supermassive black hole (SMBH) and test the SMBH binary hypothesis proposed for this source., Comment: 15 pages, 7 figures, accepted for publication in ApJ

Transfer learning of StyleGAN has recently shown great potential to solve diverse tasks, especially in domain translation. Previous methods utilized a source model by swapping or freezing weights during transfer learning, however, they have limitations on visual quality and controlling source features. In other words, they require additional models that are computationally demanding and have restricted control steps that prevent a smooth transition. In this paper, we propose a new approach to overcome these limitations. Instead of swapping or freezing, we introduce a simple feature matching loss to improve generation quality. In addition, to control the degree of source features, we train a target model with the proposed strategy, FixNoise, to preserve the source features only in a disentangled subspace of a target feature space. Owing to the disentangled feature space, our method can smoothly control the degree of the source features in a single model. Extensive experiments demonstrate that the proposed method can generate more consistent and realistic images than previous works., Comment: Full CVPR 2023 paper is available at arXiv:2303.11545. Best paper of CVPRW AICC 2022 (CVPR 2022 Workshop on AI for Content Creation). The code is available at https://github.com/LeeDongYeun/FixNoise

Super-resolution suffers from an innate ill-posed problem that a single low-resolution (LR) image can be from multiple high-resolution (HR) images. Recent studies on the flow-based algorithm solve this ill-posedness by learning the super-resolution space and predicting diverse HR outputs. Unfortunately, the diversity of the super-resolution outputs is still unsatisfactory, and the outputs from the flow-based model usually suffer from undesired artifacts which causes low-quality outputs. In this paper, we propose FS-NCSR which produces diverse and high-quality super-resolution outputs using frequency separation and noise conditioning compared to the existing flow-based approaches. As the sharpness and high-quality detail of the image rely on its high-frequency information, FS-NCSR only estimates the high-frequency information of the high-resolution outputs without redundant low-frequency components. Through this, FS-NCSR significantly improves the diversity score without significant image quality degradation compared to the NCSR, the winner of the previous NTIRE 2021 challenge., Comment: CVPRW 2022, First three authors are equally contributed

We present MeqSilhouette v2.0 (MeqSv2), a fully polarimetric, time-and frequency-resolved synthetic data generation software for simulating millimetre (mm) wavelength very long baseline interferometry (VLBI) observations with heterogeneous arrays. Synthetic data are a critical component in understanding real observations, testing calibration and imaging algorithms, and predicting performance metrics of existing or proposed sites. MeqSv2 applies physics-based instrumental and atmospheric signal corruptions constrained by empirically-derived site and station parameters to the data. The new version is capable of applying instrumental polarization effects and various other spectrally-resolved effects using the Radio Interferometry Measurement Equation (RIME) formalism and produces synthetic data compatible with calibration pipelines designed to process real data. We demonstrate the various corruption capabilities of MeqSv2 using different arrays, with a focus on the effect of complex bandpass gains on closure quantities for the EHT at 230 GHz. We validate the frequency-dependent polarization leakage implementation by performing polarization self-calibration of synthetic EHT data using PolSolve. We also note the potential applications for cm-wavelength VLBI array analysis and design and future directions., Comment: accepted for publication in MNRAS