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Ionospheric Storm and Spatial Gradient Analysis for GBAS
Jeongrae Kim,Tae Hyoung Yang,Young Jae Lee,Hyang Sig Jun,Gi Wook Nam 한국항해항만학회 2006 한국항해항만학회 학술대회논문집 Vol.1 No.-
High ionospheric spatial gradient during ionospheric storm is most concern for the landing approach with GNSS (Global Navigation Satellite System) augmentation systems. In case of the GBAS (Ground-Based Augmentation System), the ionospheric storm causes sudden increase of the ionospheric delay difference between a ground facility and a user (aircraft), and the aircraft position error increases significantly. Since the ionosphere behavior and the storm effect depend on geographic location, understanding the ionospheric storm behavior at specific regional area is crucial for the GNSS augmentation system development and implementation. Korea Aerospace Research Institute and collaborating universities have been developing an integrity monitoring test bed for GBAS research and for future regional augmentation system development. By using the dense GPS (Global Positioning System) networks in Korea, a regional ionosphere map is constructed for finding detailed aspect of the ionosphere variation. Preliminary analysis on the ionospheric gradient variation during a recent storm period is performed and the results are discussed.
Extending Ionospheric Correction Coverage Area By Using A Neural Network Method
Kim, Mingyu,Kim, Jeongrae The Korean Society for Aeronautical and Space Scie 2016 International Journal of Aeronautical and Space Sc Vol.17 No.1
The coverage area of a GNSS regional ionospheric delay model is mainly determined by the distribution of GNSS ground monitoring stations. Extrapolation of the ionospheric model data can extend the coverage area. An extrapolation algorithm, which combines observed ionospheric delay with the environmental parameters, is proposed. Neural network and least square regression algorithms are developed to utilize the combined input data. The bi-harmonic spline method is also tested for comparison. The IGS ionosphere map data is used to simulate the delays and to compute the extrapolation error statistics. The neural network method outperforms the other methods and demonstrates a high extrapolation accuracy. In order to determine the directional characteristics, the estimation error is classified into four direction components. The South extrapolation area yields the largest estimation error followed by North area, which yields the second-largest error.
Predicting IGS RTS Corrections Using ARMA Neural Networks
Kim, Mingyu,Kim, Jeongrae Hindawi Limited 2015 Mathematical problems in engineering Vol.2015 No.-
<P>An autoregressive moving average neural network (ARMANN) model is applied to predict IGS real time service corrections. ARMA coefficients are determined by applying a neural network to IGS02 orbit/clock corrections. Other than the ARMANN, the polynomial and ARMA models are tested for comparison. An optimal order of each model is determined by fitting the model to the correction data. The data fitting period for training the models is 60 min. and the prediction period is 30 min. The polynomial model is good for the fitting but bad for the prediction. The ARMA and ARMANN have a similar level of accuracies, but the RMS error of the ARMANN is smaller than that of the ARMA. The RMS error of the ARMANN is 0.046 m for the 3D orbit correction and 0.070 m for the clock correction. The difference between the ARMA and ARMANN models becomes significant as the prediction time is increased.</P>
GA-ARMA Model for Predicting IGS RTS Corrections
Kim, Mingyu,Kim, Jeongrae Hindawi Limited 2017 International journal of aerospace engineering Vol.2017 No.-
<P>The global navigation satellite system (GNSS) is widely used to estimate user positions. For precise positioning, users should correct for GNSS error components such as satellite orbit and clock errors as well as ionospheric delay. The international GNSS service (IGS) real-time service (RTS) can be used to correct orbit and clock errors in real-time. Since the IGS RTS provides real-time corrections via the Internet, intermittent data loss can occur due to software or hardware failures. We propose applying a genetic algorithm autoregressive moving average (GA-ARMA) model to predict the IGS RTS corrections during data loss periods. The RTS orbit and clock corrections are predicted up to 900 s via the GA-ARMA model, and the prediction accuracies are compared with the results from a generic ARMA model. The orbit prediction performance of the GA-ARMA is nearly equivalent to that of ARMA, but GA-ARMA’s clock prediction performance is clearly better than that of ARMA, achieving a 32% error reduction. Predicted RTS corrections are applied to the broadcast ephemeris, and precise point positioning accuracies are compared. GA-ARMA shows a significant accuracy improvement over ARMA, particularly in terms of vertical positioning.</P>
GPS 전리층 모델의 장기간 가용성 및 정확도 변화 분석
김정래 ( Jeongrae Kim ),김용래 ( Yongrae Kim ) 한국항행학회 2023 韓國航行學會論文誌 Vol.27 No.6
The Klobuchar ionospheric model included in GPS navigation messages provides ionospheric correction information to single-frequency users. This ionospheric model accuracy has a significant impact on the accuracy of navigation solutions. We examine the GPS navigation messages from 1993 to 2022 and analyze their accuracy, presence of coefficients and accuracy of the Klobuchar model. Early GPS navigation messages often did not include ionospheric data, and even when they did include ionospheric models, the accuracy was often quite low. From 2002, when the accuracy of the ionospheric model was stabilized, until 2022, the accuracy of the ionospheric model is analyzed by comparing it with the ionospheric model of the International GNSS Service (IGS). Changes in accuracy per day and per year and accuracy differences along geomagnetic latitude are analyzed.
김정래 ( Jeongrae Kim ),김종우 ( Jong-woo Kim ),권순민 ( Soon-min Kwon ),박총명 ( Chong-myung Park ),정인범 ( In-bum Jung ) 한국정보처리학회 2008 한국정보처리학회 학술대회논문집 Vol.15 No.2
유비쿼터스 컴퓨팅 환경에서는 사용자의 의도를 정확히 파악하고 그에 따른 정확한 정보 또는 서비스를 제공하는 것이 중요하다. 현재 보편적으로 사용 중인 키보드와 마우스는 직관성이 결여되었거나 휴대성이 부족하므로 유비쿼터스 환경에 적합한 새로운 입력 시스템이 필요하다. 본 논문에서는 2축 가속도 센서와 2개의 압력센서를 사용하여 무선 센서네트워크 환경에서 사용자의 손동작을 감지하여 컴퓨터를 직관적으로 사용할 수 있는 유비쿼터스 환경에 적합한 입력 시스템(u-Glove)을 설계 및 구현한다.
김정래(Jeongrae Kim),박규식(Kyushik Park),김광일(Kwangil Kim) 한국자동차공학회 2009 한국자동차공학회 학술대회 및 전시회 Vol.2009 No.11
An electro-mechanical actuator is increasingly applied for the active roll control system to improve fuel efficiency and to simplify system configurations. The electric active roll control system (eABC System) has an advantage of rapid response, but it needs gear box with high reduction ratio to generate high torque for vehicle roll attitude control. This reduction gear amplifies the effect of friction and rotating inertia when the actuator rotates, and it influences negative effect on riding performance. The paper introduces some arrangements of motor and gears of the actuator for eARC system, and proposes the optimized actuator structure to improve ride feeling by estimating dynamic characteristics of each arrangement through simulating the dynamic model of the system.