• 한국해양학회지
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• v.22 no.3
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• pp.143-152
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• 1987

The digital data were obtained using Kennedy 9000 magnetic tape deck which was connected to the SMS960 side scan sonar during the field operations. The data of three consecutive survey tracks near Seongsan-po, Cheju were used for the development of this study. The softwares were mainly written in Fortran-77 using VAX 11/780 MINI-COMPUTER (CPU Memory; 4MB). The established mapping system consists of the pretreatment and the digital processing of seafloor image data. The pretreatment was necessary because the raw digital data format of the field magnetic tapes was not compatible to the VAX system. Therefore the raw data were read by the personal computer using the Assembler language and the data format was converted to IBM compatible, and next data were communicated to the VAX system. The digital processing includes geometrical correction for slant range, statistical analysis and cartography of the seafloor image. The sound speed in the water column was assumed 1,500 m/sec for the slant range correction and the moving average method was used for the signal trace smoothing. Histograms and cumulative curves were established for the statistical analysis, that was purposed to classify the backscattering strength from the sea-bottom. The seafloor image was displayed on the color screen of the TEKTRONIX 4113B terminal. According to the brief interpretation of the result image map, rocky and sedimentary bottoms were very well discriminated. Also it was shown that the backscattered acoustic pressurecorrelateswith the grain size and sorting of surface sediments.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.271-278
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• 2016

Localized atmospheric conditions between multi-reference stations can bring the tropospheric delay irregularity that becomes an error terms affecting positioning accuracy in network RTK environment. Imbalanced network error can affect the network solutions and it can corrupt the entire network solution and degrade the correction accuracy. If an anomaly could be detected before the correction message was generated, it is possible to eliminate the anomalous satellite that can cause degradation of the network solution during the tropospheric delay anomaly. An atmospheric grid that consists of four meteorological stations was used to detect an inhomogeneous weather conditions and tropospheric anomaly applied AWSs (automatic weather stations) meteorological data. The threshold of anomaly detection algorithm was determined based on the statistical weather data of AWSs for 5 years in an atmospheric grid. From the analytic results of anomaly detection algorithm it showed that the proposed algorithm can detect an anomalous satellite with an anomaly flag generation caused tropospheric delay anomaly during localized atmospheric conditions between stations. It was shown that the different precipitation condition between stations is the main factor affecting tropospheric anomalies.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.129-138
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• 2023

Acquiring precise coordinates of ground targets can be regarded as the key mission of the tactical-level military UAS(Unmanned Aerial System) operations. The coordinates deviations for the ground targets estimated from UAV (Unmanned Aerial Vehicle) images may depend on the sensor specifications and slant ranges between UAV and ground targets. It has an order of several tens to hundreds of meters for typical tactical UAV mission scenarios. In this paper, we propose a scheme that precisely acquires target coordinates from UAS by mapping image pixels to geographical coordinates based on GCP(Ground Control Points). This scheme was implemented and tested from ground control station for UAS. We took images of targets of which exact location is known and acquired the target coordinates using our proposed scheme. The experimental results showed that errors of the acquired coordinates remained within an order of several meters and the coordinates accuracy was significantly improved.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.265-270
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• 2016

Extreme tropospheric anomalies such as typhoons or regional torrential rain can degrade positioning accuracy of the GPS signal. It becomes one of the main error terms affecting high-precision positioning solutions in network RTK. This paper proposed a detection algorithm to be used during atmospheric anomalies in order to detect the tropospheric irregularities that can degrade the quality of correction data due to network errors caused by inhomogeneous atmospheric conditions between multi-reference stations. It uses an atmospheric grid that consists of four meteorological stations and estimates the troposphere zenith total delay difference at a low performance point in an atmospheric grid. AWS (automatic weather station) meteorological data can be applied to the proposed tropospheric anomaly detection algorithm when there are different atmospheric conditions between the stations. The concept of probability density distribution of the delta troposphere slant delay was proposed for the threshold determination.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.12
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• pp.1521-1528
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• 2012

The present paper provides the elastic stress intensity factors (SIFs) and the crack opening displacements (CODs) of a thick-walled pipe with a slanted axial through-wall crack. For estimating these elastic fracture mechanics parameters, systematic three-dimensional elastic finite element (FE) analyses were performed by considering geometric variables, i.e., thickness of pipe, reference crack length, and crack length ratio, affecting the SIFs and CODs. As for loading condition, the internal pressure was considered. Based on the FE results, the SIFs and CODs of slanted axial through-wall cracks in a thickwalled pipe along the crack front and the wall thickness were calculated. In particular, to calculate the SIFs of a thick-walled pipe with a slanted axial through-wall crack from those of a thick-walled pipe with an idealized axial through-wall crack, a slant correction factor representing the effect of the slant crack on the SIFs was proposed.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.189-198
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• 2022

In this present study, we investigated the effect of the offset correction factor calculation method on the sulfur dioxide (SO₂) column density in the SO₂ retrieval algorithm of the Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020. The GEMS operational SO₂ retrieval algorithm is the Differential Optical Absorption Spectroscopy (DOAS) - Principal Component Analysis (PCA) Hybrid algorithm. In the GEMS Hybrid algorithm, the offset correction process is essential to correct the absorption effect of ozone appearing in the SO₂ slant column density (SCD) obtained after spectral fitting using DOAS. Since the SO₂ column density may depend on the conditions for calculating the offset correction factor, it is necessary to apply an appropriate offset correction value. In this present study, the offset correction values were calculated for days with many cloud pixels and few cloud pixels, respectively. And a comparison of the SO₂ column density retrieved by applying each offset correction factor to the GEMS operational SO₂ retrieval algorithm was performed. When the offset correction value was calculated using radiance data of GEMS on a day with many cloud pixels was used, the standard deviation of the SO₂ column density around India and the Korean Peninsula, which are the edges of the GEMS observation area, was 1.27 DU, and 0.58 DU, respectively. And around Hong Kong, where there were many cloud pixels, the SO₂ standard deviation was 0.77 DU. On the other hand, when the offset correction value calculated using the GEMS data on the day with few cloud pixels was used, the standard deviation of the SO₂ column density slightly decreased around India (0.72 DU), Korean Peninsula (0.38 DU), and Hong Kong (0.44 DU). We found that the SO₂ retrieval was relatively stable compared to the SO₂ retrieval case using the offset correction value on the day with many cloud pixels. Accordingly, to minimize the uncertainty of the GEMS SO₂ retrieval algorithm and to obtain a stable retrieval, it is necessary to calculate the offset correction factor under appropriate conditions.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.813-821
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• 2001

While recognition of isolated units of writing, such as a character or a word, has been extensively studied, emphasis on the segmentation itself has been lacking. In this paper we propose an active segmentation method for handwritten Hangul address strings based on the Run-length code. A slant correction algorithm, which is considered as an important preprocessing step for the segmentation, is presented. Three fundamental candidate estimation functions are introduced to detect the clues on touching points, and the classification of touching types is attempted depending on the structural peculiarity of Hangul. Our experiments show segmentation performance of 88.2% on touching characters with minimal over-segmentation.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.297-304
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• 2022

The models used for ionosphere error correction in positioning using Global Navigation Satellite System (GNSS) are representatively Klobuchar model and NeQuick model. Although these models can correct the ionosphere error in real time, the disadvantage is that the accuracy is only 50-60%. In this study, a method for polynomial modeling of Global Ionosphere Map (GIM) which provides Vertical Total Electron Content (VTEC) in grid type was studied. In consideration of Ionosphere Pierce Points (IPP) of satellites with a receivable elevation angle of 15 degrees or higher on the Korean Peninsula, the target area for model generation and provision was selected, and the VTEC at 88 GIM grid points was modeled as a polynomial. The developed VTEC polynomial model shows a data reduction rate of 72.7% compared to GIM regardless of the number of visible satellites, and a data reduction rate of more than 90% compared to the Slant Total Electron Content (STEC) polynomial model when there are more than 10 visible satellites. This VTEC polynomial model has a maximum absolute error of 2.4 Total Electron Content Unit (TECU) and a maximum relative error of 9.9% with the actual GIM. Therefore, it is expected that the amount of data can be drastically reduced by providing the predicted GIM or real-time grid type VTEC model as the parameters of the polynomial model.

• Journal of Astronomy and Space Sciences
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• v.11 no.1
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• pp.71-80
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• 1994

It is generally known that the measurement of the ionospheric total electron content(TEC) by GPS can more accurately monitor the broader area of the ionosphere than other current methods. \Ve measured the TEC along a slant path considering the arrival time differences of P-code which is transmitted from GPS satellites with the modulation on two L-band carrier frequencies, L1 (1574.42MHz) and L2 (1227.60MHz). Under the assumptions that the ionosphere is uniformly distributed and its average height is 350km, we transformed the slant TEC to the vertical TEC at the point that the line-of-sight direction to GPS satellite cut across the average height of the ionosphere. Because there is no dual frequency P-code GPS receiver in Korea, we used the data observed at the TAIW GPS station ($N25^{\circ},E121.5^{\circ}$) in Taiwan which is one of the core stations in International GPS and Geodynamics Services (IGS). The TEC values obtained in this work showed a typical daily variation of the ionosphere which is high in the daytime and low in the nighttime. Our results are found to be consistent with the SOLAR-DAILY data of NOAA and the Klobuchar's model for the ionospheric correction of GPS. In addition, in the cornparision with SOLAR-DAILY data, we estimated the precision of our TEC measurement as 2 TEC.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.1-8
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• 2011

Automatic vehicle license plate recognition technology is widely used in gate control and parking control of vehicles, and police enforcement of illegal vehicles. However inherent geometric information of the license plate can be transformed in the vehicle images due to the slant and the sunlight or lighting environment. In this paper, a distortion invariant vehicle license plate extraction and recognition algorithm is proposed. First, a binary image reserving clean character strokes can be achieved by using a DoG filter. A plate area can be extracted by using the location of consecutive digit numbers that reserves distortion invariant characteristic. License plate is recognized by using neural networks after geometric distortion correction and image enhancement. The simulation results of the proposed algorithm show that the accuracy is 98.4% and the average speed is 0.05 seconds in the recognition of 6,200 vehicle images that are obtained by using commercial LPR system.