• Proceedings of the Korea Water Resources Association Conference
• /
• 2007.05a
• /
• pp.1592-1596
• /
• 2007

Accuracy of flood forecasting is an important non-structural measure on the flood control and mitigation. Hence, combination of horologic model with real time error correction became an important issue. It is one of the efficient ways to improve the forecasting precision. In this work, an approach based on Kalman Filter (KF) is proposed to continuously revise state estimates to promote the accuracy of flood forecasting results. The case study refers to the Wi River in Korea, with the flood forecasting results of Xinanjiang model. Compared to the results, the corrected results based on the Kalman filter are more accurate. It proved that this method can take good effect on hydrologic forecasting of Wi River, Korea, although there are also flood peak discharge and flood reach time biases. The average determined coefficient and the peak discharge are quite improved, with the determined coefficient exceeding 0.95 for every year.

• Progress in Medical Physics
• /
• v.20 no.4
• /
• pp.260-268
• /
• 2009

In this study, we estimated inhomogeneity correction factor in small field. And, we evaluated accuracy of treatment planning and measurement data which applied inhomogeneity correction factor or not. We developed the Inhomogeneity Correction Phantom (ICP) for insertion of inhomogeneity materials. The inhomogeneity materials were 12 types in each different electron density. This phantom is able to adapt the EBT film and 0.125 cc ion chamber for measurement of dose distribution and point dose. We evaluated comparison of planning and measurement data using ICP. When we applied to inhomogeneity correction factor or not, the average difference was 1.63% and 10.05% in each plan and film measurement data. And, the average difference of dose distribution was 10.09% in each measurement film. And the average difference of point dose was 0.43% and 2.09% in each plan and measurement data. In conclusion, if we did not apply the inhomogeneity correction factor in small field, it shows more great difference in measurement data. The planning system using this study shows good result for correction of inhomogeneity materials. In radiosurgery using small field, we should be correct the inhomogeneity correction factor, more exactly.

• Journal of Positioning, Navigation, and Timing
• /
• v.2 no.2
• /
• pp.109-114
• /
• 2013

The vulnerability of GPS to interference signals was reported in the early 2000s, and an eLORAN system has been suggested as a backup navigation system for replacing the existing GPS. Thus, relevant studies have been carried out in the United States, Europe, Korea, etc., and especially, in Korea, the research and development is being conducted for the FOC of the eLORAN system by 2018. The required performance of the eLORAN system is to meet the HEA performance, and to achieve this, it is essential to perform ASF correction based on a dLORAN system. ASF can be divided into temporal ASF, nominal ASF, and spatial ASF. Spatial ASF is the variation due to spatial characteristics, and is stored in an eLORAN receiver in the form of a premeasured map. Temporal ASF is the variations due to temporal characteristics, and are transmitted from a dLORAN site to a receiver via LDC. Unlike nominal ASF that is obtained by long-term measurement (over 1 year), temporal ASF changes in a short period of time, and ideally, real-time correction needs to be performed. However, it is difficult to perform real-time correction due to the limit of the transmission rate of the LDC for transmitting correction values. In this paper, to determine temporal ASF correction frequency that shows satisfactory performance within the range of the limit of data transmission rates, relative variations of temporal ASF in summer and winter were measured, and the stability of correction values was analyzed using the average of temporal ASF for a certain period.

• Atmosphere
• /
• v.21 no.4
• /
• pp.337-347
• /
• 2011

In this paper, we developed a detection and correction method of noisy pixels embedded in the time series of normalized difference vegetation index (NDVI) data based on the spatio-temporal continuity of vegetation conditions. For the application of the method, 25-year (1982-2006) GIMMS (Global Inventory Modeling and Mapping Study) NDVI dataset over the Korean peninsula were used. The spatial resolution and temporal frequency of this dataset are $8{\times}8km^2$ and 15-day, respectively. Also the land cover map over East Asia is used. The noisy pixels are detected by the temporal continuity check with the reference values and dynamic threshold values according to season and location. In general, the number of noisy pixels are especially larger during summer than other seasons. And the detected noisy pixels are corrected by the iterative method until the noisy pixels are completely corrected. At first, the noisy pixels are replaced by the arithmetic weighted mean of two adjacent NDVIs when the two NDVI are normal. After that the remnant noisy pixels are corrected by the weighted average of NDVI of the same land cover according to the distance. After correction, the NDVI values and their variances are increased and decreased by 5% and 50%, respectively. Comparing to the other correction method, this correction method shows a better result especially when the noisy pixels are occurred more than 2 times consistently and the temporal change rates of NDVI are very high. It means that the correction method developed in this study is superior in the reconstruction of maximum NDVI and NDVI at the starting and falling season.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.12
• /
• pp.231-238
• /
• 2023

For boost PFC (Power Factor Correction) converters, various control methods are being studied to achieve unity power factor and low THD (Total Harmonic Distortion) of AC input current. Among them, average current mode control, which controls the average value of the inductor current to follow the current reference, is the most widely used. However, nowadays, as advanced digital control becomes possible with the development of digital processors, predictive control of boost PFC converters is receiving attention. Predictive control is classified into predictive current mode control, which generates duty in advance using a predictive algorithm, and model predictive current control, which performs switching operations by selecting a cost function based on a model. Therefore, this paper simply explains the average current mode control, predictive current mode control, and model predictive current control of the boost PFC converter. In addition, current control under entire load and disturbance conditions is compared and analyzed through simulation.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2006.04a
• /
• pp.83-88
• /
• 2006

We intend to increase in efficiency of the topographic monitoring of seabed or riverbed by combined with DGPS, RTK GPS and echo sounder. For this study, we defined the error correction of the echo sounder with the experiment of water tank, which is considered the characteristic of estuary riverbed and then we developed the s/w for 3-dimensional monitoring of estuary riverbed and applied the s/w to field test and improved the various problems. On analyzing topography of estuary riverbed by combined GPS with echo sounder, the draught error which is yielded to change of length from the water surface by the movement of survey vessel to the end of the transducer was eliminated by geometrical rearrangement and we defined the correction formula, z = BM+ SAH- $DBR_{(i)}$ - DRT - ED. The sounding error about the echo sounder and characteristic of estuary riverbed was found by understanding the relation of average diameter and residual error and we defined correction formula, Y= -0.00474*In(X) -0.0045 by the regression analysis. and then we verified applicability of correction formula.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.11C
• /
• pp.1030-1036
• /
• 2006

In this paper, we present two methods of correcting bit errors in constant amplitude multi-code (CAMC) CDMA, which uses the redundant bits only. The first method is a parity-based bit correction with hard-decision, where the received signals despread into n two-dimensional structure with both horizontal parity and vertical parity. Then, an erroneous bit is corrected for each $4{\times}4$ pattern. The second method is a turbo decoding, which is modified from the decoding of a single parity check product code (SPCPC). Experimental results show that, in the second method, the redundant bits in CAMC can be fully used for the error correction and so they are not really a loss of channel bandwidth. Hence, CAMC provides both a low peak-to-average power ratio and robustness to bit errors.

• Journal of Korea Society of Industrial Information Systems
• /
• v.24 no.5
• /
• pp.1-8
• /
• 2019

In this paper, we propose a correcting method of depth pixels which are failed to measure since temporary camera error. A block is modeled to plane and sphere surfaces through measured depth pixels in the block. Depth values in the block are estimated through each modeled surface and a error for the modeled surface is calculated by comparing the original and estimated pixels, then the surface which has the least error is selected. The pixels which are failed to measure are corrected by estimating depth values through selected surface. Simulation results show that the proposed method increases the correction accuracy by an average of 20% compared with the correction method of $5{\times}5$ median method.

• Journal of Positioning, Navigation, and Timing
• /
• v.10 no.2
• /
• pp.75-82
• /
• 2021

Fields of high-precision positioning applications are growing fast across the mass market worldwide. Accordingly, the industry is focusing on developing methods of applying State-Space Representation (SSR) corrections on low-cost GNSS receivers. Among SSR correction types, this paper analyzes Safe Position Augmentation for Real Time Navigation (SPARTN) messages being offered by the SAfe and Precise CORrection DAta (SAPCORDA) company and validates positioning algorithms based on them. The first part of this paper introduces the SPARTN format in detail. Then, procedures on how to apply Basic-Precision Atmosphere Correction (BPAC) and High-Precision Atmosphere Correction (HPAC) messages are described. BPAC and HPAC messages are used for correcting satellite clock errors, satellite orbit errors, satellite signal biases and also ionospheric and tropospheric delays. Accuracies of positioning algorithms utilizing SPARTN messages were validated with two types of positioning strategies: Code-PPP using GPS pseudorange measurements and PPP-RTK including carrier phase measurements. In these performance checkups, only single-frequency measurements have been used and integer ambiguities were estimated as float numbers instead of fixed integers. The result shows that, with BPAC and HPAC corrections, the horizontal accuracy is 46% and 63% higher, respectively, compared to that obtained without application of SPARTN corrections. Also, the average horizontal and vertical RMSE values with HPAC are 17 cm and 27 cm, respectively.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.4
• /
• pp.43-48
• /
• 2015

We studied on pseudo-range correction(PRC) modeling in order to improve differential GNSS(DGNSS) accuracy. The PRC is the range correction information that provides improved location accuracy using DGNSS technique. The digital correction signal is typically broadcast over ground-based transmitters. Sometimes the degradation of the positioning accuracy caused by the loss of PRC signals, radio interference, etc. To prevent the degradation, in this paper, we have designed a PRC model through polynomial curve fitting and evaluated this model. We compared two quantities, estimations of PRC using model parameters and observations from the reference station. In the case of GPS, the average is 0.1m and RMSE is 1.3m. Most of GPS satellites have a bias error of less than ${\pm}1.0m$ and a RMSE within 3.0m. In the case of GLONASS, the average and the RMSE are 0.2m and 2.6m, respectively. Most of satellites have less than ${\pm}2.0m$ for a bias error and less than 3.0m for RMSE. These results show that the estimated value calculated by the model can be used effectively to maintain the accuracy of the user's location. However;it is needed for further work relating to the big difference between the two values at low elevation.