• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.1
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• pp.36-45
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• 2017

Abstract It is necessary to verify the properties of an inertial measurement unit in the flight environment before applying to military applications. In this paper, we presented a new approach to verify an inertial measurement unit(IMU) in regard to the performance and the robustness in flight environments for the high-dynamics vehicle systems. We proposed two methods for verification of an IMU. We confirmed normal operation of an IMU and properties in flight environment by using direct comparison method. And we proposed real time multi-navigation system to complement the first method. The proposed method made it possible to compare navigation result at the same time. Therefore, it is easy to analyze the performance of an inertial navigation system and robustness during the vehicle flight. To verify the proposed method, we carried out a flight test as well as an experimental test of flight vibration on the ground. As a result of the experiment, we confirmed flight environment properties of an IMU. Therefore, we shows that the proposed method can serve the reliability improvement of IMU.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.8
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• pp.671-677
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• 2017

A new INS/Vision integrated navigation system by using multi-vision sensors is addressed in this paper. When the total number of landmark measured by the vision sensor is smaller than the allowable number, there is possibility that the navigation filter can diverge. To prevent this problem, multi-vision concept is applied to expend the field of view so that reliable number of landmarks are always guaranteed. In this work, the orientation of camera installed are 0, 120, and -120degree with respect to the body frame to improve the observability. Finally, the proposed technique is verified by using numerical simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.6
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• pp.463-472
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• 2017

Inertial Navigation System Alignment is the process to determine direction cosine matrix which is the transformation matrix between the INS body frame and navigation frame. INS initial position value is necessary to INS attitude calculation, so that user should wait until he get such value to start the INS alignment. To remove the waiting time, we propose an alignment algorithm that immediately starts after the INS power on by using pseudo initial position input and then is completed with attitude error compensation by entering true position later. We analyse effect of INS sensor error on attitude in process of time and verify the performance and usefulness of the close-loop alignment algorithm which corrects attitude error from the change of initial position.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.2
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• pp.134-141
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• 2013

This paper explores a real-time system implementation to couple tightly StrapDown Inertial Navigation System(SDINS) and Global Positioning System(GPS) mounted on the aircraft. When implementing the SDINS/GPS coupled system in real-time processor, we have to deliberate SDINS's unique characteristics based on the ring laser gyro, and besides, lever-arm, measurements, and error compensation method. The novel modeling method is applied to system the misalignment error term of gyro to estimate the cumulative heading attitude errors while the aircraft banking to turn repeatedly. Captive Flight Test results show that the proposed modeling strategy has good performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.518-524
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• 2011

This paper presents a study on the calibration of accelerometer data in the gyroscope free inertial navigation system(GFINS) using fuzzy inference system(FIS). The conventional INS(inertial navigation system) which can measure yaw rate and linear velocity using inertial sensors as the gyroscope and accelerometer. However, the INS is difficult to design as small size and low power because it uses the gyroscope. To solve the problem, the GFINS which does not have the gyroscope have been studied actively. However, the GFINS has cumulative error problem still. Hence, this paper proposes Fuzzy-GFINS which can calibrate the data of an accelerometer using FIS consists of two inputs that are ratio between linear velocity of the autonomous ground vehicle(AGV) and the accelerometer and ratio between linear velocity of the encoders and the accelerometer. To evaluate the proposed Fuzzy-GFINS, we made the AGV with Mecanum wheels and applied the proposed Fuzzy-GFINS. In experimental result, we verified that the proposed method can calibrate effectively data of the accelerometer in the GFINS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.609-617
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• 2016

In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

• Current Industrial and Technological Trends in Aerospace
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• v.8 no.2
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• pp.76-85
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• 2010

This paper discusses recent development trends of fiber optic gyroscope (FOG) in space application. Fiber optic gyroscope utilizes Sagnac effect to measure the angular rate of a rotating object in space. Having a rather short development history compared to ring laser gyroscope (RLG), the fiber optic gyroscope, owing to the emerging technologies in fiber optic society and the digital signal processing technique, reveals itself as a noteworthy replacement of the ring laser gyroscope in the space mission. This paper summarizes the current trends of fiber optic gyroscope based on the actual products commercialized in the market over the last decades, while presenting the future development trends of the fiber optic gyroscope in the space exploration.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.139-144
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• 2016

This paper provides an overview of recent trends in sensor fusion technologies for vehicle positioning. The GNSS by itself cannot satisfy precision and reliability required by autonomous driving. We survey sensor fusion techniques that combine the outputs from the GNSS and the inertial navigation sensors such as an odometer and a gyroscope. Moreover, we overview landmark-based positioning that matches landmarks detected by a lidar or a stereo vision to high-precision digital maps.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.118-120
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• 2001

본 논문에서는 GPS(Global Positioning System)와 관성 항법 시스템(INS: Inertial Navigation System 이하 INS)을 혼합 구성한 수신보드의 운영을 위한 Embedded 운영체제를 설계하고 구현하였다. 이 운영체제는 실시간으로 인공위성과 IMU로부터 수신되어지는 Raw Measurement 획득, GPS 항법, 자세 결정, 통합항법, 위성 추적을 수행하는 태스크들을 우선순위 기반으로 처리하는 선점형(Premptive) 스케줄링 방식을 채택한 실시간 운영 체제이다. 본 논문에서는 자세 결정용 GPS와 INS를 이용한 통합시스템보드를 위한 실시간 운영체제의 개발 환경, 운영체제의 구조, 개발 내용과 실험내용에 대해 언급하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.108-118
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• 2017

This paper presents experimental results of realtime sonar-based SLAM (simultaneous localization and mapping) using probability-based landmark-recognition. The sonar-based SLAM is used for navigation of underwater robot. Inertial sensor as IMU (Inertial Measurement Unit) and DVL (Doppler Velocity Log) and external information from sonar image processing are fused by Extended Kalman Filter (EKF) technique to get the navigation information. The vehicle location is estimated by inertial sensor data, and it is corrected by sonar data which provides relative position between the vehicle and the landmark on the bottom of the basin. For the verification of the proposed method, the experiments were performed in a basin environment using an underwater robot, yShark.