• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.67-70
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• 2006

For a long time the GSM and GPS world has been living side by side. There have been some half hearted attempts to invoke the GPS unit into GSM units but performance and usability has suffered. The A-GPS approach is interesting and we wanted to verify general performance for fleet application and alarm/emergency situations. The result is now promising but still more to enhancements are anticipated. We achieved near acceptable availability (${\sim}70%$) under indoor conditions. Accuracy was as anticipated (50-100 meter) as we are using reflected signals. Time to first fix is in general good in outdoor conditions but too long for indoor conditions (45-60 seconds). We would like manufactures to put some more effort to get better performance in the future as test with Nordnav high sensitivity measurement system proves that conditions indoor are at a level where better performance should be possible.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.189-198
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• 2019

In recent years, visual-inertial odometry(VIO) algorithms have been extensively studied for the indoor/urban environments because it is more robust to dynamic scenes and environment changes. In this paper, we propose loosely coupled(LC) VIO algorithm that utilizes the velocity vectors from both visual odometry(VO) and inertial measurement unit(IMU) as a filter measurement of Extended Kalman filter. Our approach improves the estimation performance of a filter without adding extra sensors while maintaining simple integration framework, which treats VO as a black box. For the VO algorithm, we employed a fundamental part of the ORB-SLAM, which uses ORB features. We performed an outdoor experiment using an RGB-D camera to evaluate the accuracy of the presented algorithm. Also, we evaluated our algorithm with the public dataset to compare with other visual navigation systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.424-431
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• 2017

These days land vehicle navigation system is a subject of great interest. The GNSS(Global Navigation Satellite System) is the most popular technology for out door positioning. However, The GNSS is incapable of providing high accuracy and reliable positioning. For that reason, we applied Network-RTK in vehicle to improve the accuracy of GNSS performance. In this network-RTK mode, the GNSS error are significantly decreased. In this paper, we explain ntrip client program for network-RTK mode and show the result of experiments in various environments.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.323-332
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• 2023

Today, services using Positioning, Navigation, and Timing (PNT) technology are provided in various fields, such as smartphone Location-Based Service (LBS) and autonomous driving. Generally, outdoor positioning techniques depend on the Global Navigation Satellite System (GNSS), and the need for positioning techniques that guarantee positioning accuracy, availability, and continuity is emerging with advances in service. In particular, continuity is not guaranteed in urban canyons where it is challenging to secure visible satellites with standalone GNSS, and even if more than four satellites are visible, the positioning accuracy and stability are reduced due to multipath channels. Research using Low Earth Orbit (LEO) satellites is already underway to overcome these limitations. In this study, we conducted a trend analysis of LEO-PNT research, an LEO satellite-based navigation and augmentation system. Through comparison with GNSS, the differentiation of LEO-PNT was confirmed, and the system design and receiver processing were analyzed according to LEO-PNT classification. Lastly, the current status of LEO-PNT development by country and institution was confirmed.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.181-194
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• 2017

In recent years, research has been actively conducted on the navigation in an indoor environment where Global Navigation Satellite System signals are unavailable. Among them, a study performed indoor navigation by integrating pseudolite carrier and Inertial Measurement Unit (IMU) sensor. However, in this case, there was no solution for the cycle slip occurring in the carrier. In another study, cycle slip detection and compensation were performed by integrating Global Positioning System (GPS) and IMU in an outdoor environment. However, in an indoor environment, cycle slip occurs more easily and frequently, and thus the occurrence of half cycle slip also increases. Accordingly, cycle slip detection based on 1 cycle unit has limitations. Therefore, in the present study, the aforementioned problems were resolved by performing indoor navigation through the integration of pseudolite and ultra-low-cost IMU embedded in a smartphone and by performing half cycle slip detection and compensation based on this. In addition, it was verified through the actual implementation of real-time navigation.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.557-564
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• 2012

This paper presents UGV localization using multi-sensor fusion based on federated filter in outdoor environments. The conventional GPS/INS integrated system does not guarantee the robustness of localization because GPS is vulnerable to external disturbances. In many environments, however, vision system is very efficient because there are many features compared to the open space and these features can provide much information for UGV localization. Thus, this paper uses the scene matching and pose estimation based vision navigation, magnetic compass and odometer to cope with the GPS-denied environments. NR-mode federated filter is used for system safety. The experiment results with a predefined path demonstrate enhancement of the robustness and accuracy of localization in outdoor environments.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.372-378
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• 2009

For effective mobility control of unmanned ground vehicles in outdoor off-road environments, terrain cover classification technology using passive sensors is vital. This paper presents a novel method far terrain classification based on color and texture information of off-road images. It uses a neural network classifier and wavelet features. We exploit the wavelet mean and energy features extracted from multi-channel wavelet transformed images and also utilize the terrain class spatial coordinates of images to include additional features. By comparing the classification performance according to applied features, the experimental results show that the proposed algorithm has a promising result and potential possibilities for autonomous navigation.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.4
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• pp.256-265
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• 2023

This paper describes the results of the development of the submarine Free Running Model (FRM). First, the goal of development was set based on the test conditions and the test environment, and the system was obtained accordingly. The target submarine, Joubert BB2 submarine, was selected with a scale of 18.35 in accordance with the development goal. In order to conduct a submarine FRM test underwater, where communication is impossible, the FRM must operate at least semi-autonomously. For this purpose, an Extended Kalman Filter (EKF) based underwater integrated navigation system and control system using a sailplane and an X-shaped sternplane were designed respectively. In addition, a ballast system was designed to enable the model to float to the water surface in case of an emergency. To verify its propulsion, navigation, and control performance, the FRM tests were conducted in both indoor and outdoor basins. As a result, the relationship between propeller RPM and vehicle speed was derived, and it was confirmed that the navigation and control performance met the target value.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.10
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• pp.20-28
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• 2011

This paper proposes a reliable high-precision positioning system that converges a satellite navigation system and a vision system in order to resolve position errors and outdoor shaded areas, two disadvantages of a satellite navigation system. In kinematic point positioning, the number of available satellite navigation systems changes in accordance with a moving object's position. For location determination of the object, it should receive location data from at least four satellite navigation systems. However, in urban areas, exact location determination is difficult due to factors like high buildings, obstacles, and reflected waves. In order to deal with the above problem, a vision system was employed. First, determine an exact position value of a specific building in urban areas whose environment is poor for a satellite navigation. Then, identify such building by a vision system and its position error is corrected using such building. A moving object can identify such specific building using a vision system while moving, make location data values, and revise location calculations, thereby resulting in reliable high precision location determination.