• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.874-881
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• 2001

By showing the existence of the ARE solution and the convergence property of the DRE solution, this paper proves that a Kalman filter for the linear system with the unobservable bias is stable. It is also shown that the Kalman filter has a biased steady state estimation error whose covariance is affected mainly by the unobservable bias. Finally, the results are illustrated through a 2nd order system example including the inertial navigation system.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.493-495
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• 2004

In this paper, shows a research in accordance with the design the implementation of the localization system for mobile robot using INS(Inertial Navigation System) and GPS(Global Positioning System). First, a Strapdown Inertial Navigation System : SDINS is designed and implemented for low speed walking robot, by modifying Inertial Navigation System which is widely used for rocket, airplane, ship and so on. In addition, thesis proposes the localization of robot with the method of loosely coupled method by using Kalman Filter with INS/GPS integrated system to utilize assumed position and steed data from GPS.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.1
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• pp.225-233
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• 2001

This paper deals with the transfer alignment problem of SDINS(StrapDown Inertial Navigation System) subjected to roll and pitch motions of the ship. Specifically, to reduce alignment errors induced by measurement time-delay and ship body flexure, an error compensation method is suggested based on delay state augmentation and DCM(Direction Cosine Matrix) partial matching. A linearized error model for the velocity and attitude matching transfer alignment system is first derived by linearizing the nonlinear measurement equation with respect to its time delay and augmenting the delay state into the conventional linear state equations. And then DCM partial matching is properly combined to reduce effects of a ship's Y axis flexure. The simulation results show that the suggested method is effective enough resulting in considerably less azimuth alignment errors.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.133-139
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• 2007

An unmanned ground vehicle can perform its mission automatically without human control in unknown environment. To move up to a destination in various surrounding situation, navigational information is indispensible. In order to be adopted for an unmanned vehicle, the navigation box is small, light weight and low power consumption. This paper suggests navigation system using a low grade MEMS IMU for supplying position, velocity, and attitude of an unmanned ground vehicle. This system consists of low cost and light weight MEMS sensors and a GPS receiver to meet unmanned vehicle requirements. The sensors are basically integrated by loosely coupled method using Kalman filter and internal algorithms are divided into initial alignment, sensor error compensation, and complex navigation algorithm. The performance of the designed navigation system has been analyzed by real time field test and compared to commercial tactical grade GPS/INS system.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.953-957
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• 2001

This paper is concerned with a transfer alignment method for the SDINS under ship motions. Major error sources of transfer alignment are data transfer time-delay, lever-arm velocity and ship body flexure. Specifically, to reduce alignment errors induced by measurement time-delay effects, the error compensation method through delay state augmentation is suggested. A linearized error model for the velocity and attitude matching transfer alignment system is first derived by linearizing the nonliner measurement equation with respect to its time delay and augmenting the delay state into the conventional linear state equations. And then it is shown via observability analysis and computer simulations that the delay state can be estimated and compensated during ship motions resulting in considerably less alignment errors.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.177.4-177
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• 2001

In this paper, we propose a new type of nonlinear fixed interval smoothing filter which is modified from the existing nonlinear smoothing filter. A nonlinear smoothing filter is derived from two-filter formulas. For the backward filter, the propagation and update equation of error states are derived. Particularly the modified update equation of the backward filter use the estimated error terms from the forward filter. Smoothing algorithm is altered into the compatible form with the new type of the backward fitter. An advantage of the proposed algorithm is more efficient than the existing one because propagation in backward filter is very simple from the implementation point of view. We apply the proposed nonlinear smoothing ...

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.736-744
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• 2003

The GPS attitude output or carrier phase observables can be effectively utilized to compensate the attitude error of the strapdown inertial navigation system. However, when the integer ambiguity is not correctly resolved and/or a cycle slip occurs, an erroneous GPS output can be obtained. If the erroneous GPS information is directly applied to the AGPS/INS integration system, the performance of the system can be rapidly degraded. This paper proposes an AGPS/INS integration system using the triple difference carrier phase observables. The proposed integration system contains a cycle slip detection algorithm, in which inertial information is combined. Computer simulations and van test were performed to verify the proposed integration system. The results show that the proposed system gives an accurate and reliable navigation solution even when the integer ambiguity is not correct and the cycle slip occurs.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.486-486
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• 2000

This paper is concerned with a transfer alignment method for the SDINS(StrapDown Inertial Navigation System) under ship motions. Major error sources of transfer alignment are data transfer time-delay, lever-arm velocity and ship body flexure. Specifically, to reduce alignment errors induced by measurement time-delay effects, the error compensation method through delay state augmentation is suggested. A linearized error model for the velocity and attitude matching transfer alignment system is first derived by linearizing the nonlinear measurement equation with respect to its time delay and augmenting the delay state into the conventional linear state equations. And then it is shown via observability analysis and computer simulations that the delay state can be estimated and compensated during ship motions resulting in considerably less alignment errors.

• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.201-210
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• 1998

Inertial Navigation System(INS) can provide the vehicle position and velocity information using inertial sensor outputs without the use of external aids. Unfortunately INS navigation error increases with time due to inertial sensor errors, and therefore it is desirable to combine INS with external aids such as GPS, TACAN, OMEGA, and etc.. In this paper we propose an integration algorithm of commercial GPS/GLONASS and INS where an adaptive filter for signal processing of GPS/GLONASS receiver and the 12th order Kalman filter for aided strapdown INS(SDINS) we employed. Simulation results show that the proposed adaptive filter can effectively remove a randomly occurring abrupt jump due to sudden corruption of the received satellite signal and that the Kalman filter performs satisfactorily.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.369-373
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• 2001

This paper is concerned with a transfer alignment of SDINS under ship motions. To reduce alignment errors induced by the ship body flexure, an error compensation method is suggested based on velocity and DCM partial matching, and by interpreting the simulation results and comparing with the conventional velocity and quaternion partial matching, it is shown that the proposed method is effective enough to improve the azimuth alignment performance.