• Journal of Positioning, Navigation, and Timing
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• 제13권2호
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• pp.189-197
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• 2024

Galileo is a European Global Navigation Satellite System (GNSS) that has offered the Galileo Open Service since 2016. Consequently, the standardization of GNSS augmentation systems, such as Satellite Based Augmentation System (SBAS), Ground Based Augmentation System (GBAS), and Aircraft Based Augmentation System (ABAS) for Galileo signals, is ongoing. In 2023, the European Union Space Programme Agency (EUSPA) released prior probabilities of a satellite fault and a constellation fault for Galileo, which are 3×10^-5 and 2×10^-4 per hour, respectively. In particular, the prior probability of a Galileo constellation fault is significantly higher than that for the GPS constellation fault, which is defined as 1×10^-8 per hour. This raised concerns about its potential impact on GBAS integrity monitoring. According to the Global Positioning System (GPS) Standard Positioning Service Performance Standard (SPS PS), a constellation fault is classified as a wide fault. A wide fault refers to a fault that affects more than two satellites due to a common cause. Such a fault can be caused by a failure in the Earth Orientation Parameter (EOP). The EOP is used when transforming the inertial axis, on which the orbit determination is based, to Earth Centered Earth Fixed (ECEF) axis, accounting for the irregularities in the rotation of the Earth. Therefore, a faulty EOP can introduce errors when computing a satellite position with respect to the ECEF axis. In GNSS, the ephemeris parameters are estimated based on the positions of satellites and are transmitted to navigation satellites. Subsequently, these ephemeris parameters are broadcasted via the navigation message to users. Therefore, a faulty EOP results in erroneous broadcast ephemeris data. In this paper, we assess the conventional ephemeris fault detection monitor currently employed in GBAS for wide faults, as current GBAS considers only single failure cases. In addition to the existing requirements defined in the standards on the Probability of Missed Detection (PMD), we derive a new PMD requirement tailored for a wide fault. The compliance of the current ephemeris monitor to the derived requirement is evaluated through a simulation. Our findings confirm that the conventional monitor meets the requirement even for wide fault scenarios.

• 한국정보통신학회논문지
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• 제10권4호
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• pp.693-699
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• 2006

항공관측으로 얻어지는 디지털 영상은 지리정보로써의 가치를 가지기 위해서는 정밀하게 정사보정되어야 한다. 항공영상의 자동 정사보정을 위해 카메라와 함께 설치된 GPS/INS (Global Positioning System/Inertial Navigation System) 자료와 LIDAR (LIght Detection And Ranging) 지표고도 자료를 이용하였다. 본 연구에서 635개 항공영상이 생산되고 LIDAR 자료는 정사보정에 적용하기 위하여 격자영상 형태로 변환되었다. 영상 전체적으로 일정한 명도를 가지기 위해서, flat field 수정을 영상에 적용하였다. 영상은 내부방위와 GPS/INS를 이용한 외부방위를 계산하여 기하보정되고, LIDAR 지표고도 영상을 이용하여 정사보정되었다. 정사보정의 정도는 임의의 5개 영상과 LIDAR 반사강도 영상에서 50개 지상기준점을 수집하여 검증되었다. 검정된 결과로써 RMSE (Root Mean Square Error)는 화소 해상도의 단지 2배에 해당하는 0.387 m를 도출하였다. 높은 정도를 가진 자동 항공영상 정사보정 방법은 항공영상 산업에 적용 가능할 것이다.

• Journal of Astronomy and Space Sciences
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• 제18권2호
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• pp.129-136
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• 2001

GPS (Global Positioning System)를 이용한 정밀 응용분야에 있어 위성의 궤도력과 지구자전 상수 (Earth Orientation Parameter, EOP)의 정밀도는 매우 중요한 요소이다. 특히, GPS를 이용한 대기강시 등 신속한 정밀자료처리가 요구되는 응용분야는 실시간 또는 정밀하게 예측된 위성의 궤도력과 EOP를 필요로 한다. 이를 위해 IGS (International GPS Service)는 매일 3시, 15시 (UTC)에 IGU (lGS Ultra Rapid Product)를 생성하여 서비스하고 있다. IGU는 48시간의 정밀 궤도력과 EOP로 구성되어 있는데, 처음 24시간은 관측한 데이터를 처리하여 산출하고 다음 24시간은 예측을 통해서 산출한 값으로 이루어져 있다. 본 논문에서는 독자적인 URP (Ultra Rapid Product)를 산출하기 위한 프로세싱 전략을 수립하고 타당성을 검증하였다. 이를 위해 32개 IGS 관측소의 48시간 관측 자료를 처리하여 URP를 산출하고, 그 결과를 IGS에서 제공하는 여러 정밀 궤도력 및 EOP와 비교하였다.

• 한국측량학회지
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• 제17권4호
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• pp.321-330
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• 1999

본 연구는 수치사진측량학과 전산기 시각 분야의 연구를 통하여 발전하고 있는 영상정합기법을 적용하여 사진지표의 관측과 위치결정을 자동화하는데 목적이 있다. 이러한 자동화과정에서 주된 문제점은 계산을 수행하는데 있어서의 시간을 최소화하고 위치결정의 정확도를 높이는 것이다. 본 연구에서는 스캐닝과정과 기준점의 절대적인 위치를 구하는 과정을 제외하고 영상 정합기법과 영상처리 기법을 이용하여 내부표정 과정을 자동화하였다. 본 연구에 의해서 개발된 체계를 근거리사진측량에 의한 결과를 적용하였으며 결과를 분석한 결과 최대 54%까지 계산시간이 절감되었다. 내부표정과정동안 사진지표의 관측에 대해서, Laplacian of Gaussian 변환과 휴 변환을 각각 영상의 중심점의 정확한 결정을 위하여 적용하였으며, 상관계수영상정합과 최소제곱 영상정합기법을 사진지표의 정확한 위치결정을 위하여 사용하였다. 영상피라미드의 개념을 사진지표의 자동 관측과정에 적용하여 계산시간을 절감할 수 있었다.

• Journal of Positioning, Navigation, and Timing
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• 제11권4호
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• pp.351-360
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• 2022

Autonomous vehicles require precise knowledge of their position, velocity and orientation in all weather and traffic conditions in any time. And, these information is effectively used for path planning, perception, and control that are key factors for safety of vehicle driving. For this purpose, a high precision GNSS technology is widely adopted in autonomous vehicles as a core localization and navigation method. However, due to the lack of infrastructure as well as cost issue regarding GNSS correction data communication, only a few high precision GNSS technology will be available for future commercial autonomous vehicles. Recently, a high precision GNSS sensor that is based on a Broadcast-RTK system to dramatically reduce network maintenance cost by utilizing the existing broadcasting network is released. In this paper, we present the performance test result of the broadcast-RTK-based commercial high precision GNSS receiver to test the feasibility of the system for autonomous driving in Korea. Massive measurement campaigns covering of Korea region were performed, and the obtained measurements were analyzed in terms of ambiguity fixing rate, integer ambiguity loss recovery, time to retry ambiguity fixing, average correction information update rate as well as accuracy in comparison to other high precision systems.

• Journal of Communications and Networks
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• 제18권5호
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• pp.837-845
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• 2016

Providing a customer with tailored location-based services (LBSs) is a fundamental problem. For location-estimation techniques with radio-based measurements, LBS applications are widely available for mobile devices (MDs), such as smartphones, enabling users to run multi-task applications. LBS information not only enables obtaining the current location of an MD but also provides real-time push-pull communication service. For indoor environments, localization technologies based on radio frequency (RF) pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching approaches, a considerable amount of time and work is spent in indoor environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposes an indoor positioning approach, which involves using Asus Xtion to facilitate capturing RF signals during an offline site survey. The depth information obtained using Asus Xtion is utilized to estimate the locations and predict the received signal strength (RF information) at uncertain locations. The proposed approach effectively reduces not only the time and work costs but also the computing complexity involved in determining the orientation and RF during the online positioning phase by estimating the user's location by using a smartphone. The experimental results demonstrated that more than 78% of time was saved, and the number of samples acquired using the proposed method during the offline phase was twice as much as that acquired using the conventional method. For the online phase, the location estimates have error distances of less than 2.67 m. Therefore, the proposed approach is beneficial for use in various LBS applications.

• 제어로봇시스템학회논문지
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• 제22권8호
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• pp.603-609
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• 2016

This paper presents an optimally designed master device mechanism for teleoperated interventional robotic system. The interventional procedures using the teleoperated robotic system and the physicians' requirements are summarized. The master device should implement 5-DOF motion including 2-DOF translational motion for the entry position control, 2-DOF rotational motion for the orientation control, and 1- DOF translational motion for needle insertion. The handle assembly includes a 1-DOF translational mechanism for needle insertion and buttons for operation mode selection. The mechanisms for the 2-DOF translational motion and the 2-DOF rotational motion are designed using motors and brakes based on the various mechanisms to satisfy all the above requirements, respectively. Absolute position sensors are adopted to implement automatic initial positioning and orientation matching at the first step of needle insertion.

• 한국측량학회지
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• 제39권6호
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• pp.541-548
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• 2021

최근 농업, 산림관리, 해안환경 모니터링 등 다양한 분야에서 다분광 카메라의 활용, 특히 드론에 탑재되어 활용되는 사례가 증대되고 있다. 산출되는 다분광 영상은 위치정보를 위해 주로 드론에 탑재된 GPS (Global Positioning System)나 IMU (Inertial Measurement Unit) 센서를 이용해 지리참조(georeferencing)되는데, 보다 높은 정확도를 위해서는 직접 측량한 지상 기준점을 이용하기도 한다. 하지만, 직접 측량에 드는 비용 및 시간으로 인해 또는 직접 접근이 어려운 지역에 대해서는 지상 참조값을 활용하지 않고 지리참조를 수행해야하는 경우가 자주 발생하게 된다. 본 연구는 지상기준점이 가용하지 않은 경우에 다분광카메라로부터의 영상의 지리참조 정밀도를 향상시키기 위해 같이 탑재된 고해상도 RGB카메라의 영상을 활용하는 방안에 대하여 연구한다. 드론 영상은 우선 번들조정을 통해 카메라의 외부표정 요소를 추정하였고, 이를 지상 기준점을 이용한 경우의 외부표정 및 위치결과와 비교하였다. 실험결과, 고해상도 영상을 포함하여 번들조정을 하게 될 경우, 다분광 카메라 영상을 단독으로 활용할 때보다, 다분광 카메라 영상의 지리참조 오차가 비약적으로 감소하였음을 확인하였다. 추가로 한 지상 지점에서 드론으로의 방향각을 추정할 때의 오차를 분석한 결과, 마찬가지로 고해상도 RGB영상을 포함하여 번들조정하게 되면 기존의 방향각 오차가 한 단위이상 감소하는 것으로 나타났다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.684-687
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• 2006

Airborne imagery must be precisely orthorectified to be used as geographical information data. GPS/INS (Global Positioning System/Inertial Navigation System) and LIDAR (LIght Detection And Ranging) data were employed to automatically orthorectify airborne images. In this study, 154 frame airborne images and LIDAR vector data were acquired. LIDAR vector data were converted to raster image for employing as reference data. To derive images with constant brightness, flat field correction was applied to the whole images. The airborne images were geometrically corrected by calculating internal orientation and external orientation using GPS/INS data and then orthorectified using LIDAR digital elevation model image. The precision of orthorectified images was validated using 50 ground control points collected in arbitrary selected five images and LIDAR intensity image. In validation results, RMSE (Root Mean Square Error) was 0.365 smaller then two times of pixel spatial resolution at the surface. It is possible that the derived mosaicked airborne image by this automatic orthorectification method is employed as geographical information data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권5호
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• pp.1339-1355
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• 2023

Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.