• Journal of Positioning, Navigation, and Timing
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• 제11권4호
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• pp.251-261
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• 2022

The Centimeter Level Augmentation Service (CLAS) is the Precise Point Positioning (PPP) - Real Time Kinematic (RTK) correction service utilizing the Quasi-Zenith Satellite System (QZSS) L6 (1278.65 MHz) signal to broadcast the Global Navigation Satellite System (GNSS) error corrections. Compact State-Space Representation (CSSR) corrections for mitigating GNSS measurement error sources such as satellite orbit, clock, code and phase biases, tropospheric error, ionospheric error are estimated from the ground segment of QZSS CLAS using the code and carrier-phase measurements collected in the Japan's GNSS Earth Observation Network (GEONET). Since the CLAS service begun on November 1, 2018, users with dedicated receivers can perform cm-level precise positioning using CSSR corrections. In this paper, CLAS-based VRS-RTK performance evaluation was performed using Global Positioning System (GPS) observables collected from the refence station, TSK2, located in Japan. As a result of performing GPS-only RTK positioning using the open-source software CLASLIB and RTKLIB, it took about 15 minutes to resolve the carrier-phase ambiguities, and the RTK fix rate was only about 41%. Also, the Root Mean Squares (RMS) values of position errors (fixed only) are about 4cm horizontally and 7 cm vertically.

• Journal of Positioning, Navigation, and Timing
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• 제10권4호
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• pp.243-251
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• 2021

Real-Time Kinematic (RTK) is a phase-based differential GNSS technique and uses additional observations from permanent reference stations to mitigate or eliminate effects like atmospheric delays or satellite clocks and orbit errors. In particular, as the position accuracy required in the fields of autonomous vehicles and drones is gradually increasing, the demand for RTK-based precise navigation that can provide cm-level position is increasing. Recently, with the rapid growth of the open-source software market, the use of open-source software for building navigation system of unmanned vehicles, which is difficult to mount an expensive GNSS receivers, is gradually increasing. RTKLIB is an open-source software package that can perform RTK positioning and is widely used for research and education purposes. However, since the performance and stability of RTK algorithm of RTKLIB is inevitably inferior to that of commercial GNSS receivers, users need to verify whether RTKLIB can satisfy the navigation performance requirements of unmanned vehicles. Therefore, in this paper, the performance evaluation of the RTK positioning algorithm of RTKLIB was performed using GNSS observation data acquired in a dynamic environment. Therefore, in this paper, the RTK positioning performance of RTKLIB was evaluated using GNSS observation data acquired in a dynamic environment. Our results show that the current RTK algorithm of RTKLIB is not suitable for precise navigation of unmanned vehicles.

• 센서학회지
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• 제32권5호
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• pp.267-274
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• 2023

LiDAR, one of the most important sensing methods used in mobile robots and cars with assistive/autonomous driving functions, is used to locate surrounding obstacles or to build maps. For real-time path generation, the detection of potholes or puddles on the driving surface is crucial. To achieve this, we used the coordinates of the reflection points provided by LiDAR as well as the intensity information to classify water areas, which was achieved by applying a linear regression method to the intensity distribution. The rationale for using the LiDAR index as an input variable for linear regression is presented, and we demonstrated that it is not affected by errors in the distance measurement value. Because of LiDAR vertical scanning, if the reflective surface is not uniform, it is divided into different groups according to the intensity distribution, and a mathematical basis for this is presented. Through experiments in an outdoor driving area, we could distinguish between flat ground, potholes, and puddles, and kinematic analysis was performed to calculate the maximum width that could be crossed for a given vehicle body size and wheel radius.

• 로봇학회논문지
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• 제19권1호
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• pp.23-30
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• 2024

This paper studies a GPS error filtering method that takes into account the continuity of the ongoing path to enhance the safety of autonomous agricultural mobile robots. Real-Time Kinematic Global Positioning System (RTK-GPS) is increasingly utilized for robot position evaluation in outdoor environments due to its significantly higher reliability compared to conventional GPS systems. However, in orchard environments, the robot's current position obtained from RTK-GPS information can become unstable due to unknown disturbances like orchard canopies. This problem can potentially lead to navigation errors and path deviations during the robot's movement. These issues can be resolved by filtering out GPS information that deviates from the continuity of the waypoints traversed, based on the robot's assessment of its current path. The contributions of this paper is as follows. 1) The method based on the previous waypoints of the traveled path to determine the current position and trajectory. 2) GPS filtering method based on deviations from the determined path. 3) Finally, verification of the navigation errors between the method applying the error filter and the method not applying the error filter.

• 한국전자파학회논문지
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• 제26권4호
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• pp.404-413
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• 2015

대공 레이다에서 표적의 분류는 대 탄도탄 모드 수행의 가장 중요한 부분 중 하나이다. 대 탄도탄 모드에서는 항공기와 탄도탄을 분류하여 각 표적에 따른 대응 방법을 결정한다. 표적 분류의 속도와 정확도는 적의 공격에 대한 대응 능력과 직접적인 관련이 있으므로, 효율적이고 정확한 표적 분류 알고리즘이 필수적이다. 일반적으로, 레이다는 표적 분류를 위해 JEM(Jet Engine Modulation) 및 HRR(High Range Resolution), ISAR(Inverse Synthetic Array Radar) 영상 등을 사용하는데, 이러한 기법들은 표적 분류를 위한 별도의(광대역 등) 레이다 파형과 DB(Data Base) 및 분류 알고리즘을 요구한다. 본 논문은 별도의 파형 없이 실제 다기능 레이다에서 적용 가능한 표적 분류 기법을 제안한다. 특징 벡터로 추적 시 얻은 표적의 운동학적인 특징(kinematics features)을 이용하여 레이다 하드웨어 및 시간 관점에서 레이다 자원을 아끼고, 구현이 간단하여 빠르고 상대적으로 정확한 퍼지 논리(fuzzy logic)를 분류 알고리즘으로 사용하여 실제 환경에서의 적용성을 높였다. 항공기의 실측 데이터와 탄도탄의 모의 신호를 사용하여 제안한 분류 알고리즘의 성능과 적합성을 증명하였다.

• 인간식물환경학회지
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• 제24권4호
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• pp.441-450
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• 2021

Background and objective: The purpose of study is to analyze the three-dimensional (3D) structure by creating a 3D model for green spaces in a park using unmanned aerial vehicle (UAV) images. Methods: After producing a digital surface model (DSM) and a digital terrain model (DTM) using UAV images taken in Mureung Park in Chuncheon-si, we generated a digital tree height model (DHM). In addition, we used the mean shift algorithm to test the classification accuracy, and obtain accurate tree height and volume measures through field survey. Results: Most of the tree species planted in Mureung Park were Pinus koraiensis, followed by Pinus densiflora, and Zelkova serrata, and most of the shrubs planted were Rhododendron yedoense, followed by Buxus microphylla, and Spiraea prunifolia. The average height of trees measured at the site was 7.8 m, and the average height estimated by the model was 7.5 m, showing a difference of about 0.3 m. As a result of the t-test, there was no significant difference between height values of the field survey data and the model. The estimated green coverage and volume of the study site using the UAV were 5,019 m² and 14,897 m³, respectively, and the green coverage and volume measured through the field survey were 6,339 m² and 17,167 m³. It was analyzed that the green coverage showed a difference of about 21% and the volume showed a difference of about 13%. Conclusion: The UAV equipped with RTK (Real-Time Kinematic) and GNSS (Global Navigation Satellite System) modules used in this study could collect information on tree height, green coverage, and volume with relatively high accuracy within a short period of time. This could serve as an alternative to overcome the limitations of time and cost in previous field surveys using remote sensing techniques.

• 한국수자원학회논문집
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• 제41권9호
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• pp.895-905
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• 2008

유역의 수문현상을 해석하기 위해서는 다양한 지형자료와 수문 시계열자료가 필요하다. 최근 들어 DEM(Digital Elevation Model)과 수자원 주제도와 같은 지형자료 뿐만 아니라 수치예보자료 및 강우레이더의 관측자료와 같은 수문 시계열자료 또한 격자 형태로 제공되고 있으며, 이를 활용한 수문분석에 대한 다양한 연구가 이루어지고 있다. 본 연구에서는 이러한 격자형 자료를 이용하여 효과적으로 단기간의 강우-유출 현상을 모의하기 위한 물리적 기반의 분포형 강우-유출 모형인 GRM(Grid based Rainfall-runoff Model)을 개발하였다. 지표면 유출과 하도 유출의 모의는 운동파 방정식을 이용하고 있으며, 침투량 산정을 위해서 Green-Ampt 모형을 이용하고 있다. 지배방정식은 유한 체적법을 이용하여 이산화 하였으며, TDMA(TriDiagonal Matrix Algorithm) 방법을 이용하여 연립방정식을 풀고, 비선형 항에 대해서는 Newton-Raphson 방법으로 반복 계산함으로써 수렴해를 도출하였다. 개발된 모형은 단순화된 가상의 유역에 대해서 적용한 결과를 $Vflo^{TM}$ 모형의 모의결과와 비교함으로써 타당성을 검토하였다. 또한 위천 유역의 적용을 통해 모형의 검증 및 실제 유역에 대한 적용성을 검토하였으며, 모의결과는 관측유량의 재현성이 높은 것으로 나타났다.

• 대한공간정보학회지
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• 제10권4호
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• pp.69-76
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• 2002

오늘날에 정보는 토목공학에서 매우 중요하다. 대개 이 정보는 측량 및 지형공간정보체계로부터 획득된다. 또한 이 정보는 지능형교통체계(ITS), 항법, 시설물 관리, 그리고 수치지도제작, 기타 등의 분야에서 매우 중시되고 또한 앞으로 다양한 분야에서 응용될 것이다. 그리고 측량분야에서, GPS 위성이 새로이 도입되어 중요한 역할을 하고 있다. 본 연구에서는 GPS 위성을 이용한 측위기술 중 하나인 실시간 동적측량(RTK)을 대학의 평면도 제작에사용하였다. 이를 통해 화단 일부분과 도로에 대한 정보를 회득할 수 있었지만 주위 건물에 대해서는 회득이 불가능 하였다. 그러므로 이것은 전채 작업에서 작업의 효율성을 저하시키게 된다. 그래서 이런 경우 토탈스테이션, 평판, 그리고 데오도라이트 등이 기타 보조장비가 사용되어야 할 것으로 기대된다.

• Journal of Positioning, Navigation, and Timing
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• 제4권1호
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• pp.33-41
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• 2015

Compact Network Real-Time Kinematic (RTK) is a method that combines compact RTK and network RTK, and it can effectively reduce the time and spatial de-correlation errors. A network RTK user receives multiple correction information generated from reference stations that constitute a network, calculates correction information that is appropriate for one's own position through a proper combination method, and uses the information for the estimation of the position. This combination method is classified depending on the method for modeling the GPS error elements included in correction information, and the user position accuracy is affected by the accuracy of this modeling. Among the GPS error elements included in correction information, tropospheric delay is generally eliminated using a tropospheric model, and a combination method is then applied. In the case of a tropospheric model, the estimation accuracy varies depending on the meteorological condition, and thus eliminating the tropospheric delay of correction information using a tropospheric model is limited to a certain extent. In this study, correction information modeling accuracy performances were compared focusing on the Low-Order Surface Model (LSM), which models the GPS error elements included in correction information using a low-order surface, and a modified LSM method that considers tropospheric delay characteristics depending on altitude. Both of the two methods model GPS error elements in relation to altitude, but the second method reflects the characteristics of actual tropospheric delay depending on altitude. In this study, the final residual errors of user measurements were compared and analyzed using the correction information generated by the various methods mentioned above. For the performance comparison and analysis, various GPS actual measurement data were collected. The results indicated that the modified LSM method that considers actual tropospheric characteristics showed improved performance in terms of user measurement residual error and position domain residual error.