• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.8
• /
• pp.329-335
• /
• 2018

Satellite images, which are widely used in various applications, are very useful for monitoring the surface of the earth. Since satellite data is obtained from a remote sensor, it contains a lot of noise and errors depending on observation weather conditions during data acquisition and sensor malfunction status. Since the accuracy of the data affects the accuracy and reliability of the data analysis results, noise removal and data restoration for high quality data is important. In this study, we propose a reconstruction system that models the time dependent dynamic characteristics of satellite data using a multi-period harmonic model and performs adaptive data restoration considering the spatial correlation of data. The proposed method is a real-time restoration method and thus can be employed as a preprocessing algorithm for real-time reconstruction of satellite data. The proposed method was evaluated with both simulated data and MODIS NDVI data for six years from 2011 to 2016. Experimental results show that the proposed method has the potentiality for reconstructing high quality satellite data.

• Atmosphere
• /
• v.21 no.1
• /
• pp.85-93
• /
• 2011

UK Met Office Unified Model (UM) is a grid model applicable for both global and regional model configurations. The Met Office has developed a 4D-Var data assimilation system, which was implemented in the global forecast system on 5 October 2004. In an effort to improve its Numerical Weather Prediction (NWP) system, Korea Meteorological Administration (KMA) has adopted the UM system since 2008. The aim of this study is to provide the basic information on the effects of satellite data assimilation on UM performance by conducting global satellite data denial experiments. Advanced Tiros Operational Vertical Sounder (ATOVS), Infrared Atmospheric Sounding Interferometer (IASI), Special Sensor Microwave Imager Sounder (SSMIS) data, Global Positioning System Radio Occultation (GPSRO) data, Air Craft (CRAFT) data, Atmospheric Infrared Sounder (AIRS) data were assimilated in the UM global system. The contributions of assimilation of each kind of satellite data to improvements in UM performance were evaluated using analysis data of basic variables; geopotential height at 500 hPa, wind speed and temperature at 850 hPa and mean sea level pressure. The statistical verification using Root Mean Square Error (RMSE) showed that most of the satellite data have positive impacts on UM global analysis and forecasts.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.6
• /
• pp.11-20
• /
• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.5
• /
• pp.162-177
• /
• 2020

The perception of traffic environment based on various sensors in autonomous driving system has a direct relationship with driving safety. Recently, as the perception model based on deep neural network is used due to the development of machine learning/in-depth neural network technology, a the perception model training and high quality of a training dataset are required. However, there are several realistic difficulties to collect data on all situations that may occur in self-driving. The performance of the perception model may be deteriorated due to the difference between the overseas and domestic traffic environments, and data on bad weather where the sensors can not operate normally can not guarantee the qualitative part. Therefore, it is necessary to build a virtual road environment in the simulator rather than the actual road to collect the traning data. In this paper, a training dataset collection process is suggested by diversifying the weather, illumination, sensor position, type and counts of vehicles in the simulator environment that simulates the domestic road situation according to the domestic situation. In order to achieve better performance, the authors changed the domain of image to be closer to due diligence and diversified. And the performance evaluation was conducted on the test data collected in the actual road environment, and the performance was similar to that of the model learned only by the actual environmental data.

• Atmosphere
• /
• v.26 no.2
• /
• pp.347-356
• /
• 2016

Radiosonde is an observation equipment that measures pressure (geopotential height), temperature, relative humidity and wind by being launched up from the ground. Radiosonde data which serves as an important element of weather forecast and research often causes a bias in a model output due to accuracy and sensitivity between the different manufacturers. Although Korean Meteorological Administration (KMA) and several institutes have conducted routine and intensive radiosonde observations, very few studies have been done before on the characteristics of radiosonde performance. Analyzing radiosonde observation data without proper understanding of the unique nature of those sensors may lead to a significant bias in the analysis of results. To evaluate performance and reliability of radiosonde, we analyzed the differences between two sensors made by the different manufacturers, which have been used in the campaign of Experiment on Snow Storm At Yeongdong (ESSAY). We improved a couple of methods to launch the balloon being attached with the sensors. Further we examined cloud-layer impacts on temperature and humidity differences for the analysis of both sensors' performance among various weather conditions, and also compared daytime and nighttime profiles to understand temporal dependence of meteorological sensors. The overall results showed that there are small but consistent biases in both temperature and humidity between different manufactured sensors, which could eventually secure reliable precisions of both sensors, irrespective of accuracy. This study would contribute to an improved sounding of atmospheric vertical states through development and improvement of the meteorological sensors.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.49 no.2
• /
• pp.1-6
• /
• 2012

In recent years global climate change of hurricanes and torrential rains are going to significantly, that increase damages to property and human life. The disasters have been several claimed in every field. In future, climate changes blowing are keen to strike released to the world like in several movies. Reducing the damage of long-term weather phenomena are emerging with predicting changes in weather. In this study, it is shown how to predict the red tide phenomenon with multiple linear regression analysis and artificial neural network techniques. The red tide phenomenon causing risk could be reduced by filtering sensor data which are transmitted and forecasted in real time. It could be ubiquitous driven custom marine information service system, and forecasting techniques to use throughout the meteorological disasters to minimize damage.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.15 no.2
• /
• pp.208-214
• /
• 2012

The spectral radiance received by a remote sensor is consisted of the self-emitted component directly from the target surface, the reflected component of the solar irradiance at the target surface, and the scattered component by the atmosphere without ever reaching the object surface. In general, the self-emitted component is the most important part in the infrared signatures from the target. We measured the solar irradiation, sky irradiation, air temperature, wind velocity, wind direction, relative humidity, and atmospheric pressure together with the surface temperatures of rectangular parallelepiped targets. The measured diurnal surface temperature variations on the three different rectangular parallelepiped targets constructed by the steel, aluminum and bakelite are obtained at the same time intervals. The measured surface temperature results show that the top surface temperature of bakelite recorded up tp $7.6^{\circ}C$ higher than that of aluminium and $6.1^{\circ}C$ higher than that of steel at 11 AM on the sunny condition. A complete set of measured data including the surface temperature of rectangular parallelepiped targets together with the detailed weather information can be a valuable reference for future study.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.5
• /
• pp.11-18
• /
• 2021

The small radio frequency tracking radar is a tracking system with a radio frequency sensor that identifies a target through all-weather radio frequency signal processing for a target and searches, detects and tracks the target for the major target. In this paper, we describe the development of a board equipped with TMS320C6678 and XILINX FPGA (Field Programmable Gate Array), a high-speed multi-core DSP that acquires target information through all-weather radio frequency and identifies a target through real-time signal processing. We propose DSP-FPGA combination architecture for DSP and FPGA selection and signal processing, and also explain the design of SRIO for high-speed data transmission.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.1
• /
• pp.221-228
• /
• 2018

Big data is an important keyword in World's Fourth Industrial Revolution in public and private division including IoT(Internet of Things), AI(Artificial Intelligence) and Cloud system in the fields of science, technology, industry and society. Big data based on services are available in various fields such as transportation, weather, medical care, and marketing. In particular, in the field of sports, various types of bio-signals can be collected and managed by the appearance of a wearable device that can measure vital signs in training or rehabilitation for daily life rather than a hospital or a rehabilitation center. However, research on big data with vital signs from wearable devices for training and rehabilitation for baseball players have not yet been stimulated. Therefore, in this paper, we propose a system for baseball infield and outfield players, especially which can store and analyze the momentum measurement vital signals based on big data.

• The Journal of the Korea Contents Association
• /
• v.7 no.3
• /
• pp.176-186
• /
• 2007

As SAR data have the strong point that is not influenced by weather or light amount in comparison with optical sensor data, they are highly useful for temporary analysis and can be collected in time of unforeseen circumstances like disaster. This study is to extract DEM from L-band data of JERS-1 SAR imagery using InSAR and DInSAR processing techniques. As a result of analyzing the extracted coherence and interferogram images, it was shown that the DInSAR 3-pass method produces more suitable coherence values than the InSAR method. The accuracies of DEM extracted from the SAR data were evaluated by employing the DEM derived from the digital topographic maps of 1:5000 scale as reference data. And it was ascertained that baselines between antenna locations largely affect the accuracy of extracted DEM.