• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.888-893
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• 2005

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors(accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range flight missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using star tracker. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the boundedness of position and attitude errors.

• 제어로봇시스템학회논문지
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• 제9권7호
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• pp.556-562
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• 2003

This paper presents new attitude error differential equations to define attitude errors as the rotation vector for inertial navigation systems. Attitude errors are defined with the rotation vector between the reference coordinate frame and the platform coordinate frame, and Platform dynamics to the reference coordinate frame due to platform torque command errors are defined. Using these concepts for attitude error definition and platform dynamics, we have derived attitude error differential equations expressed in original nonlinear form for GINS and SDINS and showed that these are equivalent to attitude error differential equations expressed in known linear form. The relation between attitude errors defined by the rotation vector and attitude errors defined by quaternion is clearly presented as well.

• 한국항행학회논문지
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• 제21권1호
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• pp.138-144
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• 2017

본 논문에서는 INS/GPS결합 시스템에서 GPS가 기만신호 또는 지형지물에 의한 가시선이 제한되어 위성의 기하학적 배치가 저하되는 조건을 고려하였고, 통합항법 성능을 향상시키기 위한 방법을 제안하였다. 먼저 GPS의 DOP에 측정 공분산 이 연동되는 가변 공분산 확장 칼만필터(VCEKF)를 제시하였다. 그리고 몬테칼로 시뮬레이션을 통하여 EKF와 VCEKF를 사용한 통합항법 시스템의 항법성능을 분석하였다. DOP 값이 낮은 경우보다 DOP값이 높을 경우에 VCEKF가 확정 공분산을 사용하는 EKF보다 우수한 추정 성능을 보임을 확인할 수 있었다.

• 한국항공우주학회지
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• 제41권6호
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• pp.481-487
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• 2013

GPS/INS 항법시스템의 설치에 있어서 대다수의 경우 GPS 수신기 안테나는 차량의 외부에 설치하게 되고 IMU는 내부에 설치하게 된다. Lever Arm 오차는 이와 같이 센서의 장착 위치 차이로 인하여 발생하는 구조적인 오차에 해당한다. Lever Arm 오차는 항법성능에 직접적으로 영향을 주기 때문에 적절한 보상이 반드시 필요하다. 본 논문에서는 GPS와 INS의 속도 측정치를 활용하여 임의의 위치에 장착된 두 센서의 Lever Arm 오차를 효과적으로 추정하고 보상하는 방식을 제안하였다. 실험을 통해 제안한 알고리즘의 타당성을 검증하였으며, 항체의 회전운동 구간에서 Lever Arm 오차 보상이 특히 중요함을 보였다.

• Journal of Positioning, Navigation, and Timing
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• 제9권4호
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• pp.387-395
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• 2020

Accuracy of an integrated Global Positioning System (GPS) / Inertial Navigation System (INS) relies heavily on the visibility of GPS satellites. Especially, its accuracy is dramatically degraded in urban canyon due to signal obstructions due to large structures. In this paper, we propose a new integrated positioning system that effectively combines INS, GPS, ultrasonic sensor, and barometer in GPS-denied environments. In the proposed system, the ultrasonic sensor provides velocity information along the forward direction of moving vehicle. The barometer output provides height information compensated for the pressure variation due to fast vehicle movements. To evaluate the performance of the proposed system, an experiment was carried out by mounting the proposed system on a test car. By the experiment result, it was confirmed that the proposed system bears good potential to maintain positioning accuracy in harsh urban environments.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1632-1640
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• 2021

In order to improve target tracking performance of the conventional electro-optical tracking system (EOTS) in the high speed and high maneuvering vehicle, an EOTS navigation algorithm is proposed, in which an inertial measurement unit(IMU) is included and navigation results of the vehicle are used. The proposed algorithm integrates vehicle's navigation results and the IMU and the time-delay and the scale factor errors are augmented into the integrated Kalman filter. In order to evaluate the proposed navigation algorithm, a land vehicle navigation experiments were performed a navigation grade navigation system, TALIN4000 and a tactical grade IMU, LN-200 and a equipment for roll motion were loaded on the land vehicle. The performance evaluation results show that the proposed algorithm effecting works in high maneuvering environment and for the time-delay.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.580-585
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• 2005

A QRT(Quad-Rotor Type) hovering robot system is developed for quick detection and observation of the circumstances under calamity environment such as indoor fire spots. The UAV(Unmanned Aerial Vehicle) is equipped with four propellers driven by each electric motor, an embedded controller using a DSP, INS(Inertial Navigation System) using 3-axis rate gyros, a CCD camera with wireless communication transmitter for observation, and an ultrasonic range sensor for height control. The developed hovering robot shows stable flying performances under the adoption of RIC(Robust Internal-loop Compensator) based disturbance compensation and the vision based localization method. The UAV can also avoid obstacles using eight IR and four ultrasonic range sensors. The VTOL(Vertical Take-Off and Landing) flying object flies into indoor fire spots and sends the images captured by the CCD camera to the operator. This kind of small-sized UAV can be widely used in various calamity observation fields without danger of human beings under harmful environment.

• 정보통신설비학회논문지
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• 제9권3호
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• pp.92-101
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• 2010

Energy efficiency and safe mobility are the two key constituents of the future automobile. The technologies that enable these features are now heavily dependent upon information and communication technology rather than traditional auto-mechanical technology. This paper presents an exploratory project 'Smart&Green Vehicle Project' at Western Michigan University which is to improve the geographical location accuracy of vehicles and to study various applications of making such location data available. Global Positioning System (GPS), Inertial Navigation System (INS), Vehicular Ad-hoc Network (VANET) technology, and data fusion among these technologies are investigated. Testing and evaluation is done on systems which will gather vehicular positioning data during GPS signal loss. Vehicles in urban settings do not acquire accurate positioning data from GPS alone; therefore there is a need for exploration into technology that can assist GPS in urban settings. The goal of this project is to improve the accuracy of positioning data during a loss of GPS signal. Controlled experiments are performed to gather data which aided in assessing the feasibility of these technologies for use in vehicular platforms.

• 대한교통학회지
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• 제25권2호
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• pp.157-165
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• 2007

본 연구에서는 GPS(Global Positioning System), INS(Inertial Navigation System), DMI(Distance Measuring Unit) 등 각종 센서를 장착한 차량을 이용하여 차량의 위치정보와 자세정보를 취득하고, 취득된 차량의 주행정보를 이용하여 도로 종단선형을 분석할 수 있는 알고리즘을 개발하였다. 개발된 종단선형 분석 알고리즘은 도로의 종단경사, 종단곡선 시종점 및 도로 종단곡선 길이 등을 분석할 수 있고, 종단경사와 종단곡선을 모형화하였다. 또 개발한 알고리즘의 현장 적용성을 검증하기 위하여, 실제 도로에서 취득한 데이터를 이용하여 종단선형을 분석하였고, 이 결과를 도면과 비교하였다.