• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.1
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• pp.16-23
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• 2011

This paper suggests a motion compensation technique using GPS/IMU data in order to compensate for phase error caused by undesired motion of radar platform. An actual flight trajectory would be deviate from an ideal straight-constant trajectory with a constant velocity for SAR imaging, due to pitch, roll and yaw motion of aircraft caused by turbulence. This leads to blurred SAR images due to inter-pulse phase errors as well as along-track velocity errors. If the motion compensation is carried out to reduce those errors, SAR image quality can be significantly improved. Simulation results show that the motion compensation technique introduced in this paper is an effective tool to improve SAR image quality against severe motion of radar platform.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.590-593
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• 2004

Extraction of ocean surface current velocity offers important physical oceanographic parameters especially on understanding ocean environment. Although Remote Sensing techniques were highly developed, the investigation of ocean surface current using Synthetic Aperture Radar (SAR) is not an easy task. This paper presents the results of ocean surface current observation using Doppler Centroid of ERS-1 SAR data obtained off the coast of Korea peninsula. We employed the concept, in which Doppler frequency shift and the ocean surface current are closely related, to evaluate ocean surface current. Moving targets cause Doppler frequency shift of the back scattered radar waves of SAR, thus the line-of-sight velocity component of the scatters can be evaluated. The Doppler frequency shift can be measured by estimating the difference between Doppler Centroid of raw SAR data and reference Doppler Centroid. Theoretically, the Doppler Centroid is zero; however, squinted antenna which is affected by several physical factors causes Doppler Centroid to be nonzero. The reference Doppler Centroid can be obtained from measurements of sensor trajectory, attitude and Earth model. The estimated Doppler Centroid was compensated by considering the accurate attitude estimation of ERS-1 SAR. We could verify the correspondence between the estimated ocean surface current and observed in-situ data in the error bound.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.33-34
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• 2015

The voyage and cargo volume passing through the Arctic route (NSR) have been gradually increased. The ship-ice collision is one of the most biggest factors threatening the safety navigation of ice-going ships. A lot of researchers are trying to reveal the ship-ice collision mechanism. In this study, some tests that a model ship is forced to collide with disk-shaped synthetic ice are carried out in a towing tank. Then, ice floe's motion (velocity and trajectory) is measured by machine vision inspection.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.293-299
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• 2021

Purpose: To accelerate magnetic resonance fingerprinting (MRF) by developing a flexible deep learning reconstruction method. Materials and Methods: Synthetic data were used to train a deep learning model. The trained model was then applied to MRF for different organs and diseases. Iterative reconstruction was performed outside the deep learning model, allowing a changeable encoding matrix, i.e., with flexibility of choice for image resolution, radiofrequency coil, k-space trajectory, and undersampling mask. In vivo experiments were performed on normal brain and prostate cancer volunteers to demonstrate the model performance and generalizability. Results: In 400-dynamics brain MRF, direct nonuniform Fourier transform caused a slight increase of random fluctuations on the T2 map. These fluctuations were reduced with the proposed method. In prostate MRF, the proposed method suppressed fluctuations on both T1 and T2 maps. Conclusion: The deep learning and iterative MRF reconstruction method described in this study was flexible with different acquisition settings such as radiofrequency coils. It is generalizable for different in vivo applications.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.4
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• pp.285-293
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• 2020

In this paper, to improve Synthetic Aperture Radar (SAR) image quality, the effect of time synchronization error in the EGI/IMU (Embedded GPS/INS, Inertial Measurement Unit) integrated system is analyzed and state augmentation is applied to compensate it. EGI/IMU integrated system is widely used as a SAR motion measurement algorithm, which consists of EGI mounted to obtain the trajectory and IMU mounted on the SAR antenna. In an EGI/IMU integrated system, a time synchronization error occurs when the clocks of the sensors are not synchronized. Analysis of the effect of time synchronization error on navigation solutions and SAR images confirmed that the time synchronization error deteriorates SAR image quality. The state augmentation is applied to compensate for this and as a result, the SAR image quality does not decrease. In addition, by analyzing the performance and the observability of the time synchronization error according to the maneuver, it was confirmed that the time-variant maneuver such as rotational motion is necessary to estimate the time synchronization error adequately. In order to reduce the influence of the time synchronization error on the SAR image, the time synchronization error must be compensated by performing maneuver changing over time such as a rotation before SAR operation.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1037-1043
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• 2003

This paper describes a speech synthesis technique using a diphone as an unit phoneme. Speech synthesis is basically accomplished by concatenating unit phonemes, and it's major problem is discontinuity at the connection part between unit phonemes. To solve this problem, this paper proposes a new spectral smoothing technique which reflects not only formant trajectories but also distribution characteristics of spectrum and human's acoustic characteristics. That is, the proposed technique decides the quantity and extent of smoothing by considering human's acoustic characteristics at the connection part of unit phonemes, and then performs spectral smoothing using weights calculated along a time axis at the border of two diphones. The proposed technique reduces the discontinuity and minimizes the distortion which is caused by spectral smoothing. For the purpose of performance evaluation, we tested on five hundred diphones which are extracted from twenty sentences using ETRI Voice DB samples and individually self-recorded samples.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1069-1080
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• 2022

The tropospheric ozone is a pollutant that causes a great deal of damage to humans and ecosystems worldwide. In the event that ozone moves downwind from its source, a localized problem becomes a regional and global problem. To enhance ozone monitoring efficiency, geostationary satellites with continuous diurnal observations have been developed. The objective of this study is to derive the Tropospheric Ozone Movement Vector (TOMV) by employing continuous observations of tropospheric ozone from geostationary satellites for the first time in the world. In the absence of Geostationary Environmental Monitoring Satellite (GEMS) tropospheric ozone observation data, the GEOS-Chem model calculated values were used as synthetic data. Comparing TOMV with GEOS-Chem, the TOMV algorithm overestimated wind speed, but it correctly calculated wind direction represented by pollution movement. The ozone influx can also be calculated using the calculated ozone movement speed and direction multiplied by the observed ozone concentration. As an alternative to a backward trajectory method, this approach will provide better forecasting and analysis by monitoring tropospheric ozone inflow characteristics on a continuous basis. However, if the boundary of the ozone distribution is unclear, motion detection may not be accurate. In spite of this, the TOMV method may prove useful for monitoring and forecasting pollution based on geostationary environmental satellites in the future.