• 한국컴퓨터정보학회논문지
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• 제29권4호
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• pp.115-123
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• 2024

본 논문에서는 교통약자의 운행지원을 위하여 내비게이션 정보와 웨어러블 밴드를 융합한 진동 알림 시스템을 제안한다. 기존 내비게이션 시스템은 정상인을 기준으로 길 안내와 위치정보 제공에 초점이 맞춰져 있어 표준시력 및 자극의 인지 지연의 장애가 있는 교통약자에게는 안전 및 편 Stick PC의 애플리케이션으로 전송하고 변환된 신호를 웨어러블 밴드로 전달한다. 웨어러블 밴드 의성 저하로 인한 교통사고 유발의 위험성을 가진다. 제안하는 시스템은 내비게이션 운행 정보를 에 전달된 신호는 유형에 따라 좌회전, 우회전, 과속 및 이벤트 등의 구분된 진동 신호를 통하여 운전자의 운행가이드 정보로 제공된다. 구현된 시스템의 성능평가 결과, 메시지의 송수신은 안정적인 상태를 유지하였고 내비게이션 정보 수신에 따른 진동 신호의 반응속도는 평균 1.875ms로 유효한 결과를 보였다. 또한, 한국장애인고용공단 일자리 안정부 장애우를 대상으로 1개월간의 현장 적응 평가에서도 편리성, 오작동, 추가 및 개선 사항과 접근용이성 측면에서 평균 9.16점으로 매우 긍정적인 사용자 평가를 받았다. 향후 카메라와 차량의 센서를 추가하여 차량 접근이나 객체 인식 등에 대한 알림 기능을 추가하여 차량 내부와 외부의 안전에 대한 인식을 높이고, 시력 및 인지 지연 장애가 있는 운전자의 안전한 주행 환경을 구축하기 위한 연구를 계속할 계획이다.

• 한국항행학회논문지
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• 제20권5호
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• pp.433-439
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• 2016

저가형 GNSS (global navigation satellite system) 수신 모듈에 DGNSS (differential GNSS) 서비스를 적용하기 위한 방안으로 거리 영역의 보정정보를 위치 영역으로 투영한 후, stand-alone으로 산출한 위치에 적용하는 DGNSS-CP 방식이 제안된 바 있다. DGNSS-CP 를 상용 수신기 또는 휴대폰에 적용하기 위해서는 항법 방정식의 관측행렬을 이용하여 위치영역 투영 방정식을 구성하므로, 각 위성의 시선벡터를 산출하여야 한다. GNSS 항법 메시지, 배치 정보 등이 시선벡터 산출을 위하여 사용되는데, 각 방법에 따라 정확도와 연산량 등의 성능에 차이가 발생한다. 본 연구에서는 제시된 두 가지 시선벡터 산출 방식에 따라 DGNSS-CP의 성능에 어떠한 영향을 끼치는지 확인하기 위하여, Septentrio PolaRx4 Pro 수신기에서 stand-alone mode 로 저장된 데이터에 해당 알고리즘을 적용하였고, 배치 정보를 사용하는 방법이 궤도정보를 사용하는 방법에 비해 정확도 면에서는 그 성능이 RMS (root mean square) 0.1 m 가량 저하되는 반면, 연산량은 약 1/15수준으로 줄일 수 있음을 확인하였다.

• 한국해양학회지:바다
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• 제23권4호
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• pp.204-217
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• 2018

본 연구에서는 이내비게이션 시스템이 장착된 연안 및 국제여객선을 활용하여 효율적으로 해양환경관측을 실시하고 관측된 해양 환경 빅데이터를 분석할 수 있는 방안을 제시하였다. 먼저, 이내비게이션 시스템과 운영 개념을 소개하고, 우리나라 연안의 해양환경모니터링 현황을 개괄한 후, 기존 관측망의 단점을 보완하고 장점을 강화할 수 있도록 이내비게이션을 활용한 해양환경모니터링 관측방법과 관측요소(기상, 물성, 유속 및 수심)를 제안하였다. 또한, 이내비게이션 시스템이 장착된 여객선에서 관측한 자료를 실시간으로 분석하는 시공간 혼합효과모형, 앙상블기법 및 무요소기법과 같은 해양빅데이터 분석 기법을 제안하였다. 본 연구는 연안 선박과 소형어선에 중점을 둔 한국형 이내비게이션 추진에 도움이 될 것으로 기대한다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.33-37
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• 2006

Since 1993, the civil aviation community through RTCA (Radio Technical Commission for Aeronautics) and the ICAO (International Civil Air Navigation Organization) have been working on the definition of GNSS augmentation systems that will provide improved levels of accuracy and integrity. These augmentation systems have been classified into three distinct groups: Aircraft Based Augmentation Systems (ABAS), Space Based Augmentation Systems (SBAS) and Ground Based Augmentation Systems (GBAS). The last one is an implemented system to support Air Navigation in CAT-I approaching operation. It consists of three primary subsystems: the GNSS Satellite subsystem that produces the ranging signals and navigation messages; the GBAS ground subsystem, which uses two or more GNSS receivers. It collects pseudo ranges for all GNSS satellites in view and computes and broadcasts differential corrections and integrity-related information; the Aircraft subsystem. Within the area of coverage of the ground station, aircraft subsystems may use the broadcast corrections to compute their own measurements in line with the differential principle. After selection of the desired FAS for the landing runway, the differentially corrected position is used to generate navigation guidance signals. Those are lateral and vertical deviations as well as distance to the threshold crossing point of the selected FAS and integrity flags. The Department of Applied Science in Naples has create for its study a virtual GBAS Ground station. Starting from three GPS double frequency receivers, we collect data of 24h measures session and in post processing we generate the GC (GBAS Correction). For this goal we use the software Pegasus V4.1 developed from EUROCONTROL. Generating the GC we have the possibility to study and monitor GBAS performance and integrity starting from a virtual functional architecture. The latter allows us to collect data without the necessity to found us authorization for the access to restricted area in airport where there is one GBAS installation.

• 한국해양공학회지
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• 제35권1호
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• pp.91-97
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• 2021

Marine accidents caused by ships have brought about economic and social losses as well as human casualties. Most of these accidents are caused by small and medium-sized ships and are due to their poor conditions and insufficient equipment compared with larger vessels. Measures are quickly needed to improve the conditions. This paper discusses a video-integrated collision prediction and fall detection system to support the safe navigation of small- and medium-sized ships. The system predicts the collision of ships and detects falls by crew members using the CCTV, displays the analyzed integrated information using automatic identification system (AIS) messages, and provides alerts for the risks identified. The design consists of an object recognition algorithm, interface module, integrated display module, collision prediction and fall detection module, and an alarm management module. For the basic research, we implemented a deep learning algorithm to recognize the ship and crew from images, and an interface module to manage messages from AIS. To verify the implemented algorithm, we conducted tests using 120 images. Object recognition performance is calculated as mAP by comparing the pre-defined object with the object recognized through the algorithms. As results, the object recognition performance of the ship and the crew were approximately 50.44 mAP and 46.76 mAP each. The interface module showed that messages from the installed AIS were accurately converted according to the international standard. Therefore, we implemented an object recognition algorithm and interface module in the designed collision prediction and fall detection system and validated their usability with testing.

• 대한전기학회논문지
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• 제41권9호
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• pp.1071-1084
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• 1992

In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

• 제어로봇시스템학회논문지
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• 제2권3호
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• pp.200-208
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• 1996

This paper describes the mechanism, guidance, sensor system, and navigation algorithm of METRO, a free ranging mobile robot. METRO is designed for use in structured surroundings or factory environments rather than unstructured natural environments. An overview of the physical configuration of the mobile robot is presented as well as a description of its sensor system, an omnidirectional laser range finder. Except for the global path planning algorithm, a guidance and a navigation algorithm with a local path planning algorithm are used to navigate the mobile robot. In METRO the computer support is divided into a supervisor with image processing and local path planning and a slave with motor control. The free ranging mobile robot is self-controlled and all processing being performed on board.

• 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%.

• ETRI Journal
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• 제45권5호
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• pp.758-767
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• 2023

In this study, we introduce a loosely coupled relative position estimation method that utilizes a decentralized ultrawideband (UWB), Global Navigation Support System and inertial navigation system for flight controllers (FCs). Key obstacles to multidrone collaboration include relative position errors and the absence of communication devices. To address this, we provide an extended Kalman filter-based algorithm and module that correct distance errors by fusing UWB data acquired through random communications. Via simulations, we confirm the feasibility of the algorithm and verify its distance error correction performance according to the amount of communications. Real-world tests confirm the algorithm's effectiveness on FCs and the potential for multidrone collaboration in real environments. This method can be used to correct relative multidrone positions during collaborative transportation and simultaneous localization and mapping applications.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.71-76
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• 2006

With the rapid development of spatial infrastructure in US, Europe, Japan, China and India, there is no doubt that the next generation Global Navigation Satellite System (GNSS) will improve the integrity, accuracy, reliability and availability of the position solution. GNSS is becoming an essential element of personal, commercial and public infrastructure and consequently part of our daily lives. However, the applicability of GPS in supporting a range of location-sensitive applications such as location based services in an urban environment is severely curtailed by the interference of the 3D urban settings. To characterize and gain in-depth understanding of such interferences and to be able to provide location-based optimization alternatives, a high-fidelity 3D urban model of Melbourne CBD built with ArcGIS and large scale high-resolution spatial data sets is used in this study to support a comprehensive simulation of current and future GNSS signal performance, in terms of signal continuity, availability, strength, geometry, positioning accuracy and reliability based on a number of scenarios. The design, structure and major components of the simulator are outlined. Useful time-stamped spatial patterns of the signal performance over the experimental urban area have been revealed which are valuable for supporting location based services applications, such as emergency responses, the optimization of wireless communication infrastructures and vehicle navigation services.