• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.1
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• pp.41-48
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• 2019

This paper deals with a method of aligning an aircraft fuselage and an inertial navigation sensor using three-dimensional coordinates obtained by an optical method. In order to verify the feasibility, we introduce the method to accurately align the coordinate system of the inertial navigation sensor and the aircraft reference coordinate system. It is verified through simulation that reflects the error level of the measuring device. In addition, optimization method based alignment algorithm is proposed for connection between optical sensor and inertial navigation sensor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.293-294
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• 2011

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.121-126
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• 2017

Tracking system is essential for Image Guided Surgery(IGS). Optical Tracking System(OTS) is widely used to IGS for its high accuracy and easy usage. However, OTS doesn't work when occlusion of marker occurs. In this paper sensor data fusion with OTS and Inertial Navigation System(INS) is proposed to solve this problem. The proposed system improves the accuracy of tracking system by eliminating gaussian error of the sensor and supplements the disadvantages of OTS and IMU through sensor fusion based on Kalman filter. Also, sensor calibration method that improves the accuracy is introduced. The performed experiment verifies the effectualness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.509-515
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• 2006

This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using electro-optical sensor. The proposed scheme uses the position or the attitude information from the sensor. For each case, Kalman filter model is derived and implemented. To show the effectiveness of the present compensation scheme, computer simulations have been carried out resulting in the boundedness of position and attitude errors.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.673-683
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• 2010

This study investigates Terrain Aided Inertial Navigation(TAIN) which consists of Inertial Navigation System (INS) with the optical sensor for precise planetary landing. Image processing is conducted to extract the feature points between measured terrain data and on-board implemented terrain information. The navigation algorithm with Iterated Extended Kalman Filter(IEKF) can compensate for the navigation error, and provide precise navigation information compared to single INS. Simulation results are used to demonstrate the feasibility of integration to accomplish precise planetary landing. The proposed navigation approach can be implemented to the whole system coupled with guidance and control laws.

• Proceedings of the KIEE Conference
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• 1998.07e
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• pp.1843-1845
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• 1998

Gyroscope is a very important core sensor as a rotation sensor in inertial space, in inertial guidance and navigation system on aeronautics. Plane, vessel and so on for civilian and millitary applications. Research and development of fiber optic gyroscope began in 1976 and focused on improving the gyroscope's sensitivity to rotation. bias performance and reducing noise. We have developed a Interferometric Fiber Optic' Gyroscope using a integrated-optic-circuit (IOC), which is operating with closed-loop electronic circuit. This paper describes the scheme of optical part and electronic part and also test results of this fiber optic gyroscope using a integrated-optic-circuit (IOC). The performance have been achieved as long-term bias drift of $1.73^{\circ}/h$.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.2
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• pp.95-100
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• 2013

Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.661-662
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• 2008

• Proceedings of the KIEE Conference
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• 1998.07e
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• pp.1840-1842
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• 1998

Gyroscope is a very important core sensor, as a rotation sensor in inertial space, in inertial guidance and navigation system on aeronautics, plane, vessel and so on for civilian and millitary applications. Mechnical gyroscopes, adopting a principle of spinning a top, have been used in many application system. These mechnical gyroscopes need high power consumption, long warming time and complicated peripheral devices. But fiber-optic gyroscopes, based on the Sagnac effect, have novel advantages as small volume. simple scheme, low power consumption and high reliability. So we have developed a Intermediate grade All-fiber Optic Gyroscope, which has open-loop and minimum reciprocal configuration scheme. We have designed feedback circuits for stability of amplitude and phase using four lock-in amplifier(LIA) circuits and also used for noise limitation. This paper describes the scheme of optical part and electronic part and also test results of this all-fiber optic gyroscope. The performance have been achieved as long-term bias drift of $9.54^{\circ}/h$, random walk of $0.0317^{\circ}/\sqrt{h}$ and dynamic range of ${\pm}150\;deg/s$.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.369-378
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• 2013

This paper presents a vision/LiDAR integrated navigation system that provides accurate relative navigation performance on a general ground surface, in GNSS-denied environments. The considered ground surface during flight is approximated as a piecewise continuous model, with flat and slope surface profiles. In its implementation, the presented system consists of a strapdown IMU, and an aided sensor block, consisting of a vision sensor and a LiDAR on a stabilized gimbal platform. Thus, two-dimensional optical flow vectors from the vision sensor, and range information from LiDAR to ground are used to overcome the performance limit of the tactical grade inertial navigation solution without GNSS signal. In filter realization, the INS error model is employed, with measurement vectors containing two-dimensional velocity errors, and one differenced altitude in the navigation frame. In computing the altitude difference, the ground slope angle is estimated in a novel way, through two bisectional LiDAR signals, with a practical assumption representing a general ground profile. Finally, the overall integrated system is implemented, based on the extended Kalman filter framework, and the performance is demonstrated through a simulation study, with an aircraft flight trajectory scenario.