• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1671-1674
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• 1997

In tihs paper, an acceleratiion transformation algorithm which compensates the sculling error is proposed for strapdown inertial navigation system. The algorithm utilize the corss-product of the acceleromenter outputs and gyro outputs to keep the accuracy of the vehicle velocity under high frequency dynamic motion. From the error analysis of the algorithm, it is shown that the magnitude of estimation error is reduced by four orders.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.676-679
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• 1996

In this paper, the uniform observability and the error characteristics for stationary SDINS error are analyzed. The use of the Lyapunov transformation is proposed for transforming te conventional SDINS error model and the sufficient conditions for the uniform observability of SDINS error model are analytically derived. A complete characterization for the SDINS error characteristics during two position alignment is presented which allows us to predict the performance of two position alignment in SDINS.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.26-26
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• 2000

We study on the velocity matching algorithm for transfer alignment of inertial navigation system(INS) using robust H$_2$ filter. We suggest an uncertainty model for INS and apply the suggested discrete robust H$_2$ filter to the uncertainty model compared with kalman filter, the discrete robust H$_2$ filter is shown by simulation to have good performance of alignment time and accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.31-31
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• 2000

In this paper, Ive design and test the V/F converter for KSR-III INS using commertial INC, VFC110, AD652. The test result shows that performance of AD652 is better than that of VFC110. Through the calibration of V/F converter, we show that the designed V/F converter has a good performance and is usable for KSR-III.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.1-9
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• 2004

Inertial navigation system with hardware redundancy must use FDI(Fault Detection and Isolation) method to remove the influence of faulty sensors. Until now, several FDI methods such as PSA(Parity Space Approach), GLT(Generalized Likelihood ratio Test) and OPT(Optimal Parity vector Test) method are generally used. However, because these FDI methods only consider the situation that the system has one faulty sensor, these methods cannot be directly adapted for the system with two faulty sensors. To solve this problem, in this paper, PSA method is analyzed and based on this result, new FDI method called EPSA is proposed to consider a detection and an isolation of two faulty sensors in inertial navigation system.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.353-358
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• 2011

In this paper, we have introduced a Missile In the Loop Simulation(MILS) Software developed for the missile ground test, which is based on a commercial hard real-time operating system(OS) on Windows platform called as Real-Time eXtension(RTX). MILS software makes it possible to test overall system functions of a integrated missile on the ground in the flight conditions by real-time imitating its inertial data. By means of MILS, we have performed missiles ground tests, which result in successful real flight tests.

• Journal of Biosystems Engineering
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• v.33 no.6
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• pp.423-429
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• 2008

This study was performed to investigate the effects of inertial navigation system (INS) / global positioning system (GPS) sensor fusion for agricultural vehicle navigation. An extended Kalman filter algorithm was adopted for INS/GPS sensor fusion in an integrated mode, and the vehicle dynamic model was used instead of the navigation state error model. The INS/GPS system was consisted of a low-cost gyroscope, an odometer and a GPS receiver, and its performance was tested through computer simulations. When measurement noises of GPS receiver were 10, 1.0, 0.5, and 0.2 m ($1{\sigma}$), RMS position and heading errors of INS/GPS system at 5 m/s straight path were remarkably reduced with 10%, 35%, 40%, and 60% of those obtained from the GPS receiver, respectively. The decrease of position and heading errors by using INS/GPS rather than stand-alone GPS can provide more stable steering of agricultural equipments. Therefore, the low-cost INS/GPS system using the extended Kalman filter algorithm may enable the self-autonomous navigation to meet required performance like stable steering or more less position errors even in slow-speed operation.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.239-247
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• 2022

The existing studies on the localization in the GNSS (Global Navigation Satellite System) denied environment usually exploit low-cost MEMS IMU (Micro Electro Mechanical Systems Inertial Measurement Unit) sensors to replace the GNSS signals. However, the navigation system still requires GNSS signals for the normal environment. This paper presents an integrated GNSS/INS (Inertial Navigation System) navigation system which combines GNSS and multiple IMU sensors using extended Kalman filter in partially GNSS-denied environments. The position and velocity of the INS and GNSS are used as the inputs to the integrated navigation system. The Mahalanobis distance is used for novelty detection to detect the outlier of GNSS measurements. When the abnormality is detected in GNSS signals, GNSS data is excluded from the fusion process. The performance of the proposed method is evaluated using MATLAB/Simulink. The simulation results show that the proposed algorithm can achieve a higher degree of positioning accuracy in the partially GNSS-denied environment.

• 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.