• 한국항해항만학회지
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• 제32권2호
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• pp.127-132
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• 2008

The safety degree of navigation for collision avoidance is closely related with the combination between mariner's behavior and navigational environment. The condition of navigational environment is mainly decided by navigable waters, ship traffic, rule of road, sea state, weather and so on. Especially, the condition of navigable waters and ship traffic in navigational environment are ones of the important factors to attain safe navigation when mariners are underway and crossing, head on or overtaking situation. Thus this paper is to analyze the characteristics of mariner's behavior for collision avoidance caused by ship traffic and navigable waters by analyzing the contents of questionnaire and the results of international collaborative research. As a result, it can be concluded that the density of ship traffic and the area of navigable waters affect mariner's ship handling for collision avoidance.

• 한국항행학회논문지
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• 제23권6호
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• pp.515-521
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• 2019

차세대 지능형 교통시스템(C-ITS)은 육상교통 환경에서 차로구분 수준의 위치결정 정확도를 요구하며, 이는 위성항법시스템을 활용하는 게 가장 효과적이다. 위성항법 기반 정밀위치결정 시스템에서는 차로구분 성능의 동적환경에 대한 평가가 동반되어야 하며, 이를 위한 평가 시스템 구성이 선행 될 필요가 있다. 또한 동적인 환경에서 교통 상황이나 도로 상황에 따라 변화하는 다양한 환경에 따라 성능이 변화하기 때문에, 다양한 환경에서의 성능 검증이 필요하다. 본 논문에서는 위성항법시스템 기반의 차로구분 정밀위치 결정 성능 평가를 위한 시스템과 교통, 도로와 같은 주행환경에 따른 성능 분석을 위한 기준에 대해 설명하였다. 실제 시험 평가 구간 주행을 수행하며 수집한 데이터를 바탕으로, 수치적 성능 평가를 진행 했으며, 실제 주행 궤적과 주행영상의 비교를 통해 실제 차로 구분 성능 평가를 하여 차로구분 정밀위치결정 사용자 시스템의 평가 결과를 도출하였고, 주행환경에 따른 성능을 분석 하였다.

• 해양환경안전학회지
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• 제19권5호
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• pp.491-496
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• 2013

수면비행선박의 지위가 국제해사기구(IMO)에서 선박으로 분류하는 것으로 결론지은 이후, 국내외적으로는 몇몇 규칙과 권고 사항들이 개정 및 승인되었다. 하지만 정작 수면비행선박의 종류 및 운항특성을 고려한 항법에 관해서는 규정이 미비하고, 수면비행선박간 항법에 관련해서는 규정이 되어 있지 않다. 이러한 상황에서, 현행 법령상에 다른 선박들과 수면비행선박간의 책임 관계를 명확히 하기 위하여 서로 시계에 항법상의 수면비행선박 관련 규정을 모든 시계로의 항법상으로 이동할 것과 수면비행선박간 안전통항을 확보하기 위하여 타입 'B'와 'C'의 수면비행선박이 타입 'A'의 수면비행선박을 피항해야 한다는 규정이 신설되어야 한다고 판단된다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권1호
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• pp.12-19
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• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

• 한국항행학회논문지
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• 제20권4호
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• pp.314-320
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• 2016

관성항법시스템 (INS; inertial navigation system)은 센서 오차에 의해 유발되는 항법오차 보정을 위해 보정시스템이나 보정센서를 사용한다. 위성항법시스템 (GNSS; global navigation satellite system), 속도계 (VMS; velocity measurement sensor), 레이더는 INS를 보정하기 위해 일반적으로 사용되는 장치이다. 터널을 지나거나 전파 방해를 받아 GNSS를 사용할 수 없는 환경에서 지상항법시스템 (LNS; land navigation system)이 주로 사용하는 보정센서는 속도계이다. 속도계는 진행방향의 속도성분만 존재하고 횡축 및 종축 속도성분이 없기 때문에 속도계 보정항법을 수행 할 때 직진 주행이 요구된다. 국내는 고속도로라도 원활히 속도계 보정항법을 할 수 있는 구간이 드문데, 이는 국토 형상 및 도로 건설 조건이 속도계 보정에 필요한 직진성 유지에 적합하지 않기 때문이다. 본 논문은 직진성이 보장되지 않는 환경에서 LNS의 속도계를 사용한 보정항법을 수행할 때, 측정치의 필터 갱신 조건을 두어 성능을 개선하는 알고리즘을 제안하였다. 또한 차량탑재 시험결과를 제시하여 알고리즘의 성능을 입증하였다.

• Journal of Positioning, Navigation, and Timing
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• 제12권2호
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• pp.149-155
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• 2023

In urban areas it can be difficult to utilize global navigation satellite systems (GNSS) due to signal reflections and blockages. It is thus crucial to detect reflected or blocked signals because they lead to significant degradation of GNSS positioning accuracy. In a previous study, a classifier for global positioning system (GPS) signal reception conditions was developed using three features and the support vector machine (SVM) algorithm. However, this classifier had limitations in its classification performance. Therefore, in this study, we developed an improved machine learning based method of classifying GPS signal reception conditions by including an additional feature with the existing features. Furthermore, we applied various machine learning classification algorithms. As a result, when tested with datasets collected in different environments than the training environment, the classification accuracy improved by nine percentage points compared to the existing method, reaching up to 58%.

• Journal of Positioning, Navigation, and Timing
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• 제8권3호
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• pp.95-105
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• 2019

A method that applies space-time adaptive signal processing (STAP) algorithm based on an array antenna consisting of multiple antenna elements has been known to be effective to remove wide-band jamming signals in GPS receivers. However, the occurrence of phase distortion in navigation signals has been a problem when navigation signals, from which jamming signals are removed using STAP, are supplied to global positioning system (GPS) receivers. This paper verified the navigation performance degradation as a result of phase distortion. To mitigate this phenomenon, this paper proposes a mode switching scheme, in which a bypass mode is adopted to make the best use of the tracking performance of receivers without performing signal processing when jamming signals are not present or weak, and a STAP mode is employed when jamming signals exceed the threshold value. In this paper, the mode switching scheme is proposed for two environments: when receivers are stationary, and when receivers are moving. This paper confirmed that the performance of position error improved because phase distortion could be excluded due to STAP if the bypass mode was adopted under a condition where the jamming signal power level was below the threshold value in an environment where receivers were stationary. However, this paper also observed that the navigation failed due to the instability of tracking performance of receivers due to phase distortion that occurred at the switching time, although the number of switching could be reduced dramatically by proposing a dual threshold scheme of on- and off-thresholds that switched a mode due to the array antenna characteristics of varying gains according to the jamming signal incident direction in an environment where receivers were moving. The analysis results verified that running the STAP algorithm at all times is more efficient than the mode switching, in terms of maintaining stable navigation and ensuring position error performance, to remove jamming signals in an environment where receivers were moving.

• 한국항해항만학회지
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• 제30권3호
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• pp.253-258
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• 2006

본 논문에서는 해양레저를 즐길 수 있는 천혜의 자연조건을 가진 서남권 다도해 해역의 해양레저 기반여건 분석에 관하여 논의한다. 먼저 국내 해양 레저와 요트 산업의 현황과 문제점에 대하여 분석하고 개선 방안을 제시한다. 특히 환경 친화형의 마리나 시설을 서남권 다도해 해역에 적용하여 그 타당성을 분석한다.

• Journal of Positioning, Navigation, and Timing
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• 제11권3호
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• pp.199-208
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• 2022

Inertial Navigation System (INS)/Global Navigation Satellite System (GNSS) integrated navigation system can be used for land vehicle navigation. When the GNSS signal is blocked in a dense urban area or tunnel, however, the problem of increasing the error over time is unavoidable because navigation must be performed only with the INS. In this paper, Non-Holonomic Constraints (NHC) information is utilized to solve this problem. The NHC may correct some of the errors of the INS. However, it should be noted that NHC information is not applicable to all areas within the vehicle. In other words, the lever arm effect occurs according to the distance between the Inertial Measurement Unit (IMU) mounting position and the NHC effective point, which causes the NHC condition not to be satisfied at the IMU mounting position. In this paper, an INS/GNSS/NHC integrated navigation filter is designed, and this filter has a function to compensate for the lever arm effect. Therefore, NHC information can be safely used regardless of the vehicle's driving environment. The performance of the proposed technology is verified through Monte-Carlo simulation, and the performance is confirmed through experimental test.

• 한국산업융합학회 논문집
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• 제25권3호
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• pp.341-347
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• 2022

This paper presents a comparison result of two simultaneous localization and mapping (SLAM) algorithms for navigation that have been proposed in literature. The performances of Extended Kalman Filter (EKF) SLAM under Gaussian condition, FastSLAM algorithms using Rao-Blackwellised method for particle filtering are compared in terms of accuracy of state estimations for localization of a robot and mapping of its environment. The algorithms were run using the same type of robot on indoor environment. The results show that the Particle filter based FastSLAM has the better performance in terms of accuracy of localization and mapping. The experimental results are discussed and compared.