• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.632-637
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• 2019

Recent researches on autonomous driving of vehicles are becoming very active, and it is a trend to assist safe driving and improve driver's convenience. Autonomous vehicles are required to combine artificial intelligence, image recognition capability, and Internet communication between objects. Because mobile telecommunication networks have limitations in their processing, they can be easily implemented and scale using an easily expandable Wi-Fi network. We propose a wireless design method to construct such a vehicle control network. We propose the arrangement of AP and the software configuration method to minimize loss of data transmission / reception of mobile terminal. Through the design of the proposed network system, the communication performance of the moving vehicle can be dramatically increased. We also verify the packet structure of GPS, video, voice, and data communication that can be used for the vehicle through experiments on the movement of various terminal devices. This wireless design technology can be extended to various general purpose wireless networks such as 2.4GHz, 5GHz and 10GHz Wi-Fi. It is also possible to link wireless intelligent road network with autonomous driving.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.327-332
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• 2022

The Korea Augmentation Satellite System (KASS) is the Satellite-Based Augmentation System (SBAS) under development in Korea. KASS navigation service support navigation Safety of Life (SoL) service. KASS signal provides corrections to Global Positioning System (GPS) data received from KASS Reference Stations (KRS) and is broadcast form Geostationary Earth Orbiting (GEO) satellites to KASS users and is used by GPS/SBAS user equipment to improve the accuracy, availability, continuity and integrity of the navigation solution. Seven KRS's collect the satellite data and send them to the KASS Processing Stations (KPS) for the generation of the corrections and the monitoring the integrity. For performing its computation the KPS needs to know accurate and reliable KRS antennas coordinates. These coordinates are provided as configuration parameters to the KPS. This means that the reference frame in which the KPS work is the one represented by the set of coordinates provided as input. Therefore, the activity to maintain the accuracy of the KRS antenna coordinates is necessary, knowing that coordinates can evolve due to earth plates movements or earthquakes. In this paper, we analyzed the geodetic survey results for KRS antenna coordinates from Site Acceptance Test (SAT) #1 in December 2020 to August 2022. In the future, it is expected that these activities and planning for KRS coordinates maintenance will be produced and provided to KASS system operators for KPS configuration updates during the KASS lifetime of 15 years. Through these maintenance activities, it is expected that monitoring and analysis of unpredictable events such as earthquakes and seism will be possible in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.305-312
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• 2003

Remote sensing can provide invisible information in addition to acquire wide-view image data from space. Synthetic Aperture Radar (SAR) transmits microwave to the earth from a satellite and collects the reflected echo from the surface. Interferometric processing of SAR data can detect the subtle land deformation. The information of the surface movement by SAR is useful to monitor the volcanic activity, extended subsidence of urbanized area and the prediction of the earthquake caused by crustal deformation, and it complements the conventional levelling and GPS technique. PSInSAR (Permanent Scatterers Interferometric SAR) is one of interferometric techniques to be applied to practical projects in Japan. In this paper, the projects of land deformation monitoring are shown after the explanations of the PSInSAR principle. Tokai earthquake risk assessment is the first example. PSInSAR detects the subduction of crustal deformation of the adjacent area of new assumed epicenter region of the Tokai Earthquake. The extended subsidence of the urbanized area was implemented by using Japanese satellite data i.e. JERS that has so much data the surrounding of Japan as the archive. We examine the relationship between the geological structure and settlement at Nohbi basin including Nagoya city.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.1-11
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• 2014

Traffic congestion cost is more likely to occur in the inner city than interregional road, and it accounts for about 63.39% of the whole. Therefore, it is important to mitigate traffic congestion of the inner city. Traffic congestion in the urban could be divided into Recurrent congestion and Non-recurrent congestion. Quick and accurate detection of Non-recurrent congestion is also important in order to relieve traffic congestion. The existing studies about incident detection have been variously conducted, however it was limited to Uninterrupted Traffic Flow Facilities such as freeway. Moreover study of incident detection on the interrupted Traffic Flow Facilities is still inadequate due to complex geometric structure such as traffic signals and intersections. Therefore, in this study, incident detection model was constructed using by Artificial Neural Network to aim at urban arterial road that is interrupted traffic flow facility. In the result of the reliability assessment, the detection rate were 46.15% and false alarm rate were 25.00%. These results have a meaning as a result of the initial study aimed at interrupted traffic flow. Furthermore, it demonstrates the possibility that Non-recurrent congestion can be detected by using car navigation data such as car navigator system device.

• Spatial Information Research
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• v.17 no.3
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• pp.397-404
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• 2009

To solve the problems of distribution and quality on land gravity data, airborne gravity survey was performed in 2008 obtaining the airborne gravity data with accuracy of 1.56mGal. Since airborne gravity data is the obtained at the flight height, it is necessary to convert the airborne gravity data to the surface to combine various gravity data and compute precision geoid. In addition, Stokes' integral radius, Stokes' kernel and the radius of terrain effect computation should be optimally determined to calculate precision geoid. In this study, we made an effort to decide the optimal parameters based on the distribution and the characteristic of gravity data. Then, two geoid models were calculated using the selected parameters and the difference of geoid was calculated with mean of -16.95cm and the standard deviation of ${\pm}8.50cm$. We consider that this difference is due to the distribution and errors on the gravity data. For future work, the study on the effect of geoid with newly obtained land gravity data ship-borne gravity data and GPS/Leveling data should be conducted. Furthermore, the study on the downward continuation and terran effect calculation should be studied in detail for better precision geoid construction.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.160-165
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• 2023

In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

• International Journal of Contents
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• v.5 no.2
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• pp.59-63
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• 2009

Since it is hard to use GPS for tracking mobile user in indoor environments, much research has focused on techniques using existing wireless local area network infrastructure. Signal strength received at a fixed location is not constant, so fingerprinting approach which use pattern matching is popular. But this approach has to pay additional costs to determine user location. This paper proposes a new approach to find user's location efficiently using an index scheme. After analyzing characteristics of RF signals, the paper suggests the data processing method how the signal strength values for each of the access points are recorded in a radio map. To reduce computational cost during the location determination phase, multidimensional indexes for radio map with the important information which is the order of the strongest access points are used.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.225-232
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• 2019

The satellite-based ionospheric model consists of local first-order plane function parameters for individual satellites and provides excellent accuracy in the flat ionospheric environment of the Korean Peninsula. This paper analyzes the performance of such model under the rapid changes in the ionosphere. Rapid changes in the ionosphere were observed in Korea from September to October 2014, and a satellite-based ionosphere model was applied to Wide Area Differential GPS (WADGPS) to analyze the navigation performance and the performance of estimating ionospheric delay errors. After processing the test data, it was confirmed that there was a deterioration in navigation performance and extrapolation performance in low-latitude areas and analyzed the cause.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.95-101
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• 1998

In this paper, the historical coordinates data of origin SUWON are reviewed and determination procedures are explained with the three dimensional geocentric coordinates of ITRF94 that is determined using VLBI observations. Also three translation parameters are calculated on the origin point. The national transformation parameters between the Korean geodetic system and Korean Terrestrial Reference Frame 1994(KTRF94) system, are determined using least square methods with weigted parameter constraints. The results of transformation show that one set of parameters are applicable to fixing of a position for GPS relative positioning processing and to adjusting of a network for three dimensional geocentric coordinates(KTRF94) computing.