• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2010.04a
• /
• pp.370-371
• /
• 2010

The Long Range Navigation (LORAN) had been mainly used world-wide until GPS (Global Positioning System) activation. In particular. it was essential junctionality for the ships to sail the oceans. However, according to the industry's developing, the current accuracy of Loran is insufficient for the utilization such as the harbour approach, the land navigation and the field of precise timing. Therefore it is necessary the study on the improvement of the positioning accuracy of Loran. The method of its improvement is to measure and compensate the propagation time delay, that is, additional secondary factor (ASF) between the transmitter and user's receiver. This study shows the technique for the absolute time delay measurement without a time of coincidence (TOC) table, and represents the ASF measurement result between Pohang transmitter station(9930M) and each measure points.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.590-593
• /
• 2006

Timber inventory management includes to measure and update forest attributes, which is crucial information for private companies and public organizations in property assessment and environment monitoring. Field measurement would be accurate, but time-consuming and inefficient. For the reason, remote sensing technology has been an alternative to field measurement from an economic perspective. Among several sensors, LiDAR and Radar interferometry are known for their efficiency for forest monitoring because they are less influenced by weather and light conditions, and provide reasonably accurate vertical/horizontal measurement for a large area in a short period. For example, Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED) in the U.S. can provide tree height information and DSM. On the other hand, LiDAR DSM (the first return) and DEM (the last return) can also present tree height estimation. With respect to project site of loblolly pine plantation in Louisiana in the U.S., the accuracy of SRTM C-Band approach estimating tree height was assessed by the LiDAR approaches. In addition, SRTM X-Band and NED were also compared with the results. Plantation year in inventory GIS, which is directly related to forest age, is high correlated with the difference between SRTM C-Band and NED. As a byproduct, several stands of age mismatch could be recognized using an outlier detection algorithm, and optical satellite image (ETM+) were used to verify the mismatch. The findings of this study were (1) the confirmation of usefulness of the SRTM DSM for forest monitoring and (2) Multi-sensors- Radar, LiDAR, ETM+, MODIS can be used for accuracy improvement of forest inventory GIS altogether.

• Journal of Digital Convergence
• /
• v.18 no.2
• /
• pp.285-290
• /
• 2020

This study focus on improving the text language proficiency regarding users' written text. In order to tone up accuracy improvement in writing, Computer Assisted Language Learning(CALL) can be primarily used as one of the most efficient tools. This study proposes a English Grammar Checking Application that can improve the accuracy over the current applications. The proposed system is capable of defining the difference between a Noun and a Noun Phrase which is critical in improving grammar accuracy for those who use Englilsh as a foreign language in English writing.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.9 no.2
• /
• pp.81-91
• /
• 1991

This thesis aims to improve the analysis accuracy of remotely sensed digital imagery, and the improvement is achieved by considering the weight factors(a priori probabilities) of Bayesian MLC in the classification stage. To be concrete, Bayesian decision theory is studied from remote sensing field of view, and the equations in the n-dimensional form are derived from normal probability density functions. The amount of the misclassified pixels is extracted from probability function data using the thres-holding, and this is a basis of evaluating the classification accuracy. The results indicate that 5.21% of accuracy improvement was carried out. The data used in this study is LANDSAT TM(1985.10.21 ; 116-34), and the study area is within the administrative boundary of Seoul.

• Korean Journal of Optics and Photonics
• /
• v.17 no.3
• /
• pp.216-222
• /
• 2006

We propose the use of the Gaussian-curve fitting algorithm for the improvement of measurement accuracy in wavelengthscanned Fabry-Perot filter based demodulation systems. The peak locations of FBG sensors were calculated from the fitted curves rather than from distorted PD profiles, resulting in much better measurement accuracy than that of the highest-peak search algorithm. Also, the algorithm was proved to minimize measurement uncertainty of spectrally-distorted grating sensors. From our experimental results, a temperature resolution as small as ${\sim}0.3^{\circ}C$ was readily achieved by use of the Gaussian-curve fitting algorithm whereas the highest-peak search algorithm gave a temperature resolution larger than ${\sim}4^{\circ}C$.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.10
• /
• pp.2102-2112
• /
• 2015

In this paper, we propose a new positioning scheme for accuracy improvement of Relay-based Navigation System. The conventional relay-based system occurs larger vertical error than horizontal one due to structural characteristics that positioning references are located toward same direction and a location of user is estimated by triangulation technique. In the proposed positioning scheme, the user position is reestimated using an additional virtual reference which is generated based on position information of reference stations in navigation signals and estimated initial user position. The nearest reference station from the estimated user position is selected as a virtual reference to minimize the effect of geometrical factor. The vertical error decreases by using reference points on multi planes, therefore, accurate positioning is possible than the conventional scheme. We demonstrated that the accuracy of a user is improved through simulation results.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.751-756
• /
• 2002

Since the operation of the first satellite-based navigation services, satellite positioning has played an increasing role in both surveying and navigation, and has become an indispensable tool for precise relative positioning. However, in some situations, e.g. at a low angle of elevation, the use of satellites for navigation is seriously restricted because obstacles like buildings and mountains can block signals. As a mean to resolve this problem, the quasi-zenith satellite system has been proposed as a next-generation satellite navigation system. Quasi-zenith satellite is a system which simultaneously deploys several satellites in a quasi-zenith geostationary orbit so that one of the satellites always stay close to the zenith if viewed from a specific point on the ground of East Asia. Thus, if a position measurement function compatible with GPS is installed in the quasi-zenith and stationary satellites, and these satellites are utilized together with the GPS, four satellites can be accessed simultaneously nearly all day long and a substantial improvement in position measurement, especially in metropolitan areas, can be achieved. The purpose of this paper is to evaluate the effectiveness of quasi-zenith satellite system on positioning accuracy improvement through simulation by using precise orbital information of the satellites and a three-Dimensional digital map. Through this simulation system, it is possible to calculate the number of simultaneously visible satellites and available area of the positioning without the need of actual observation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.3
• /
• pp.478-485
• /
• 2021

An injection locking technology of a semiconductor laser is a promising technology to generate optical complex signals by adjusting optical injection parameters. The extraction of the precise injection parameters plays a key role in the generation of the optical complex signal. Rate equations of semiconductor lasers under optical injection are commonly used to map the injection parameters and the corresponding optical complex signal. The accuracy of the generated optical complex signal on the injection parameters is limited since the rate equations require a locking map-based interpolation method. We propose a novel analytic method, namely rate equation-based direct extraction method, to directly calculate the injection parameters without relying on the locking map-based interpolation method. We achieved 103-times improvement of the signal accuracy by using the proposed method compared to locking-map based interpolation method.

• Journal of Korean Society for Quality Management
• /
• v.50 no.4
• /
• pp.701-716
• /
• 2022

Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.3
• /
• pp.135-152
• /
• 2018

The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.