• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.285-294
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• 2018

In this study, we implemented the data quality monitoring algorithm which is the previous step for real-time Global Navigation Satellite System (GNSS) correction generation and compared Global Positioning System (GPS) and BeiDou System (BDS). Signal Quality Monitoring (SQM), Data QM, and Measurement QM (MQM) that are well known in Ground Based Augmentation System (GBAS) were used for quality monitoring. SQM and Carrier Acceleration Ramp Step Test (CARST) of MQM result were divided by satellite elevation angle and analyzed. The data which are judged as abnormal are removed and presented as Root Mean Square (RMS), standard deviation, average, maximum, and minimum value.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1615-1622
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• 2009

Generally, the Terminal Based Navigation System(TBNS) used embedded road data searches a path that has less qualitative than The Center Based Navigation System(CBNS). TBNS has not used real time road data but it is recently able to use it with technique such as TPEG. However, it causes to increase a cost of exploring by using real time road data for improvement quality of a path, because of limited performance. In this paper, we propose a Dynamic Heuristic to improve quality of path in the TBNS. Dynamic Heuristic(DH) is not fixed data and is dynamically modified using transferred real time road data from server. In this paper, we propose path-lading algorithm with Maximum Speed Dynamic Heuristic (DH-MAX) and do an experiment. The DH-MAX is to be used the highest speed as DH, in real map divided by same size. And proposed algorithm searches path using the priority searching only of the fixed data, but also the highest speed with real time information. In the performance test, the quality of path is enhanced but the cost of searching is increased than A* algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1029-1035
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• 2013

This paper proposes a real time lane detection algorithm using LRF (Laser Range Finder) for autonomous navigation of a mobile robot. There are many technologies for safety of the vehicles such as airbags, ABS, EPS etc. The real time lane detection is a fundamental requirement for an automobile system that utilizes outside information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. By the vision-based system, recognition of environment for three dimensional space becomes excellent only in good conditions for capturing images. However there are so many unexpected barriers such as bad illumination, occlusions, and vibrations that the vision cannot be used for satisfying the fundamental requirement. In this paper, we introduce a three dimensional lane detection algorithm using LRF, which is very robust against the illumination. For the three dimensional lane detections, the laser reflection difference between the asphalt and lane according to the color and distance has been utilized with the extraction of feature points. Also a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been verified through the real experiments.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.37-46
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• 2016

The difference between definition time of GPS (Global Positioning System) position data and actual display time of car positions on a map could reduce the accuracy of car positions displayed in PND (Portable Navigation Device)-type CNS (Car Navigation System). Due to the time difference, the position of the car displayed on the map is not its current position, so an improved method to fix these problems is required. It is expected that a method that uses predicted future positionsto compensate for the delay caused by processing and display of the received GPS signals could mitigate these problems. Therefore, in this study an analysis was conducted to correct late processing problems of map positions by mapmatching using a Kalman filter with only GPS position data and a RRF (Road Reduction Filter) technique in a light-weight CNS. The effects on routing services are examined by analyzing differences that are decomposed into along and across the road elements relative to the direction of advancing car. The results indicate that it is possible to improve the positional accuracy in the along-the-road direction of a light-weight CNS device that uses only GPS position data, by applying a Kalman filter and RRF.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.1
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• pp.81-89
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• 2013

Many of the current visual odometry algorithms suffer from some extreme limitations such as requiring a high amount of computation time, complex algorithms, and not working in urban environments. In this paper, we present an approach that can solve all the above problems using a single camera. Using a planar motion assumption and Ackermann's principle of motion, we construct the vehicle's motion model as a circular planar motion (2DOF). Then, we adopt a 1-point method to improve the Ransac algorithm and the relative motion estimation. In the Ransac algorithm, we use a 1-point method to generate the hypothesis and then adopt the Levenberg-Marquardt method to minimize the geometric error function and verify inliers. In motion estimation, we combine the 1-point method with a simple least-square minimization solution to handle cases in which only a few feature points are present. The 1-point method is the key to speed up our visual odometry application to real-time systems. Finally, a Bundle Adjustment algorithm is adopted to refine the pose estimation. The results on real datasets in urban dynamic environments demonstrate the effectiveness of our proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.89-95
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• 2017

There are a variety of apps that are finding their way. And in car navigation, we launched a product that reflects Augmented Reality technology this year. However, existing apps have problems. It is implemented in 2D or 3D, has a large error range because it has been modified in most vehicles, is not updated in real time, and car augmented reality navigation is a vehicle, and a separate device is required, etc. In this study, we implemented a smartphone app for walking directions using augmented reality, and made it possible to intuitively use a route service from a user 's location to a destination. The Dijkstra algorithm is applied to calculate the shortest path to solve the problem of finding the route with the least cost. By using this application, it is possible to use the route search service even in a data-free environment, to solve the inconvenience of the language barrier, and to update in real time, so that the latest information can be always maintained. In the future, we want to develop an app that can be commercialized by using a character in the path to promote it.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.141-144
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• 2004

Aids to Navigation have been operated and placed along coasts and navigable waters as guides to mark safe water and to assist mariners in determining their position in relation to land and hidden dangers, controled on the basis of the maine traffic survey. The traditional survey have been conducted by some methods like an ocular observation using portable radar, a on-the-spot survey, a questionnaire. But these methods must have a lot of manpower and expenses. In this paper, we have developed the module which have some real time processing functions like making a database of radar image using PC camera, saving of the vessel's track, analysis if the maine traffic tendency and the distribution of density.

• Speech Sciences
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• v.11 no.2
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• pp.181-192
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• 2004

This paper presents an efficient speech interactive agent rendering smooth car navigation and Telematics services, by employing embedded automatic speech recognition (ASR), distributed speech recognition (DSR) and text-to-speech (ITS) modules, all while enabling safe driving. A speech interactive agent is essentially a conversational tool providing command and control functions to drivers such' as enabling navigation task, audio/video manipulation, and E-commerce services through natural voice/response interactions between user and interface. While the benefits of automatic speech recognition and speech synthesizer have become well known, involved hardware resources are often limited and internal communication protocols are complex to achieve real time responses. As a result, performance degradation always exists in the embedded H/W system. To implement the speech interactive agent to accommodate the demands of user commands in real time, we propose to optimize the hardware dependent architectural codes for speed-up. In particular, we propose to provide a composite solution through memory reconfiguration and efficient arithmetic operation conversion, as well as invoking an effective out-of-vocabulary rejection algorithm, all made suitable for system operation under limited resources.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.29-35
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• 2019

This paper proposes a UAV equipped with an automatic control system for educational purposes such as navigation flight or autonomous flight. The proposed UAV is capable of automatic navigation flight and it is possible to control more precisely and delicately than existing UAV which is directly controlled. And it has the advantage that it is possible to fly in a place out of sight. In addition, the user may arbitrarily change the route or route information to use it as an educational purpose for achieving the special purpose. It also allows you to check flight status by shooting a video during flight. For this purpose, it is designed to check the image in real time using 5.8GHz video transmitter and receiver. The flight information is recorded separately and used as data to judge the normal flight after the flight. The result of the paper can be flighted along the coordinates specified using GPS information. Since it can receive real-time video, it is expected to be used for various education purposes such as reconnaissance of polluted area, achievement of special purpose, and so on.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.297-304
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• 2022

The models used for ionosphere error correction in positioning using Global Navigation Satellite System (GNSS) are representatively Klobuchar model and NeQuick model. Although these models can correct the ionosphere error in real time, the disadvantage is that the accuracy is only 50-60%. In this study, a method for polynomial modeling of Global Ionosphere Map (GIM) which provides Vertical Total Electron Content (VTEC) in grid type was studied. In consideration of Ionosphere Pierce Points (IPP) of satellites with a receivable elevation angle of 15 degrees or higher on the Korean Peninsula, the target area for model generation and provision was selected, and the VTEC at 88 GIM grid points was modeled as a polynomial. The developed VTEC polynomial model shows a data reduction rate of 72.7% compared to GIM regardless of the number of visible satellites, and a data reduction rate of more than 90% compared to the Slant Total Electron Content (STEC) polynomial model when there are more than 10 visible satellites. This VTEC polynomial model has a maximum absolute error of 2.4 Total Electron Content Unit (TECU) and a maximum relative error of 9.9% with the actual GIM. Therefore, it is expected that the amount of data can be drastically reduced by providing the predicted GIM or real-time grid type VTEC model as the parameters of the polynomial model.