• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.12-18
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• 2012

This paper presents a computation method of LOS(Line Of Sight) angle using IMU(Inertial Measurement Unit) for an antenna on aerial vehicle to point to a stationary satellite. In the overall system, the antenna is located at the front of the vehicle, and an IMU is introduced to account for body flexure dynamic. And using the differences between the position and velocity of the IMU based navigation and those of GPS/INS at the vehicle center. Kalman filter is designed to suppress Strapdown INS drift errors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.2
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• pp.101-110
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• 2000

This study focuses on examination of the availability and effectiveness about application of the differential GPS methods for navigation and acquisition of the geo-spatial information. For this, the algorithms related to a navigation solution and differential GPS were implemented in MATLAB code, a number of software simulations on test model were carried out to assess its performance, comparing the results with those obtained from the commercial software. Expecially, the results coming from tracking test on test model of the OO's WADGPS which is the commercial real-time satellite-based augmentation system via geostationary satellite (GEOs), which has been investigated with those from the above GPS methods. And also, the accuracy of absolute positioning by Navigation solution and WADGPS before and after SA-off has been compared. The above results show that DGPS methods are very reliable and efficient methods for acquisition of the geo-spatial information.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1463-1478
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• 2022

Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.49-54
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• 2023

The Global Positioning System (GPS) was developed for military purposes and developed as it is today by opening civilian signals (GPS L1 frequency C/A signals). The current satellite orbits the earth about twice a day to measure the position, and receives more than 3 satellite signals (initially, 4 to calculate even the time error). The three-dimensional position of the ground receiver is determined using the data from the radio wave departure time to the radio wave Time of Arrival(TOA) of the received satellite signal through trilateration. In the case of navigation using GPS in recent years, a location error of 5 to 10 m usually occurs, and quite a lot of areas, such as apartments, indoors, tunnels, factory areas, and mountainous areas, exist as blind spots or neutralized areas outside the error range of GPS. Therefore, in order to acquire one's own location information in an area where GPS satellite signal reception is impossible, another method should be proposed. In this study, IMU(Inertial Measurement Unit) combined with an acceleration and gyro sensor and a geomagnetic sensor were used to design a system to enable location recognition even in terrain where GPS signal reception is impossible. A method to track the current position by calculating the instantaneous velocity value using a 9-DOF IMU and a geomagnetic sensor was studied, and its feasibility was verified through production and experimentation.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.57-64
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• 2014

Recently, many human-friendly communication methods have been studied for human-machine interface(HMI) without using any physical devices. One of them is the vision-based gesture recognition that this paper deals with. In this paper, we define some gestures for interaction with objects in a predefined virtual world, and propose an efficient method to recognize them. For preprocessing, we detect and track the both hands, and extract their silhouettes from the low-resolution hand images captured by a webcam. We modeled skin color by two Gaussian distributions in RGB color space and use blob-matching method to detect and track the hands. Applying the foodfill algorithm we extracted hand silhouettes and recognize the hand shapes of Thumb-Up, Palm and Cross by detecting and analyzing their modes. Then, with analyzing the context of hand movement, we recognized five predefined one-hand or both-hand gestures. Assuming that one main user shows up for accurate hand detection, the proposed gesture recognition method has been proved its efficiency and accuracy in many real-time demos.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.345-353
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• 2015

In this paper, we proposed an information fusion method for enhancement of automatic dependent surveillance - broadcast (ADS-B) system which is one of the next generation navigation system. Although ADS-B provides better performance than traditional radar, ADS-B still has error due to dependence of global navigation satellite system (GNSS) information. In this paper, we improved the ADS-B performance using information fusion of multilateration (MLAT) and wide area multilateration (WAM). Information fusion provides accurate data compared to original data. Mostly, information fusion methods use Kalman filter or IMM(interacting multiple model) filter as a subfilter. However, we used Robust IMM filter as a subfilter to improve the aircraft tracking performance. Also, we use actual ADS-B data not virtual data to increase reliability of our information fusion method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.579-586
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• 2008

In this study, it was evaluated that the 3D tracking accuracy of basketball zone track line by real time GNSS satellite positioning methods which are VRS (Virtual Reference System), DGPS (Marine Differential GPS) and PP (Point Positioning) methods. The results of comparison between three methods over horizontal track of basketball zone, VRS, DGPS and PP methods showed ${\pm}$ several cm, ${\pm}$ m, and ${\pm}$ 2m horizontal position accuracy compared with real size respectively. And also, the grade and height deviation of the checking points on basketball zone by VRS method is very similar to the real grade and height, but results by DGPS and PP methods showed big variation and deviation in each case. We expected that VRS method using GNSS reference network will be a very useful tool compared with single based RTK method in real time accurate positioning such as precision construction fields, especially.

• Journal of Environmental Science International
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• v.31 no.10
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• pp.815-824
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• 2022

It is necessary to understand the amount of snowfall and area of snow cover of Mt. Halla to ensure the safety of mountaineers and to protect the ecosystem of Mt. Halla against climate change. However, there are not enough related studies and observation posts for monitoring snow load. Therefore, to supplement the insufficient data, this study proposes an analysis of snow load and snow cover using normalized-difference snow index. Using the images obtained from the Sentinel2 satellite, the normalized-difference snow index image of Mt. Halla could be acquired. This was examined together with the meteorological data obtained from the existing observatory to analyze the change in snow cover for the years 2020 and 2021. The normalized-difference snow index images showed a smaller snow pixel number in 2021 than that in 2020. This study concluded that 2021 may have been warmer than 2020. In the future, it will be necessary to continuously monitor the amount of snow and the snow-covered area of Mt. Halla using the normalized-difference snow index image analysis method.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.763-774
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• 2020

Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms^-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

• Journal of Environmental Impact Assessment
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• v.17 no.4
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• pp.255-262
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• 2008

For the Han-river estuary and DMZ where white-naped crane (Grus vipio; endangered migratory bird) stopover or spend winter, the habitat composition and the habitat use pattern of white-naped crane were analyzed with the position data obtained by the satellite tracking method. By the use of geographic information system (GIS), the percent composition of seven habitat categories of white naped-crane data points (n=228) was analyzed. The chi-square test showed that the white-naped crane habitat use pattern was significantly different (p<0.05) from that of random points (n=228). It means that white-naped crane select and use particular habitat area in the Han-river estuary and DMZ.