• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.608-613
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• 2006

Any input acceleration that bends RLG dithering axis causes flexure error, which is a source of the noncommutative error that can not be compensated by simply using integrated gyro sensor output. This paper introduces noncommutative error equations that define attitude errors caused by flexure errors. In this paper, flexure error is classified as sensor level error if the sensing axis coincides with the dithering axis and as system level error if the two axes do not coincide. The relationship between gyro output and the rotation vector is introduced and is used to define the coordinate transformation matrix and angular motion. Equations are derived for both sensor level and system level flexure error analysis. These equations show that RLG based INS attitude error caused by flexure is directly proportional to time, amount of input acceleration and the dynamic frequency of the vehicle.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.300-309
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• 2003

The Japanese developed the first Car navigation system in 1981 with the advent of Honda, which was known as the car inertial navigation system. Now days, It is possible to search the shortest route to and from places and arrival time using the internet via cell phone to the driver based on GIS and GPS. However, even with a good navigation system, it losses the shortest route when there is an average speed of the vehicle being between S-15 kilometers. Therefore, in order to improve the vehicle waiting time and average vehicle speed, we are suggesting an optimal green time algorithm using fuzzy adaptive control, where there are different traffic intersection lengths, and lanes. In this paper, to be able to assist the driver and forecast the optimal traffic information with regards to the road conditions; dangerous roads, construction work and estimation of arrival time at their destination using internet.

• Journal of Ocean Engineering and Technology
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• v.31 no.2
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• pp.164-169
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• 2017

Studies were performed on an ARS using SDINS's RLG and the geomatic sensor. To develop the ARS, experiments were performed to determine the characteristics of the RLG and geomatic sensor. Based on the results, to reduce the angular position errors of the RLG, which accumulate from the angular velocity data, an algorithm was studied that uses the Extended Kalman filter (EKF) to compensate the RLG data and geomatic sensor data. To verify the performance of the developed algorithm for reducing the cumulative angular errors, experiments that included the developed EKF were performed. Through these, it was shown that a drastic reduction in the angular errors of the RLG were achieved.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.102-106
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• 2013

A cooperative navigation method for cooperative flight of UAVs is proposed. The commonly used navigation method for UAVs is based on GNSS measurements. However, when it is not available by jamming or other causes, an alternative method is needed. In this paper, it is shown that UAVs equipped with inertial sensors, passive sensor and wireless communication link can perform accurate navigation through sharing information with each other. Firstly, the appropriate roles for sensors and wireless communication link are assigned. Secondly, a filter to perform navigation cooperative is constructed. Finally, the boundedness of estimation error of the filter under small initial estimation error is analyzed. The simulation results show that the proposed method can reduce navigation errors effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1106-1116
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• 2011

LINS (Laser Inertial Navigation System) consists of RLG (Ring Laser Gyroscopes)/accelerometers and provides real-time navigation information to the target system. Therefore it is very important to make a decision in the real time whether LINS is in the normal operation or not. That is called a fault detection method. In this paper, we propose the fault detection method of LINS based on the overlapping model. We also show that the fault detection probability is increased through overlapping the hardware model and the software model. It is verified through the long-term operation and RAM (Reliability Availability Maintainability) analysis of LINS that the fault detection method proposed in this paper is able to detect about 97% of probable system failures.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1254-1255
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• 2011

최근 무선통신기반 열차제어시스템의 국산화 개발이 진행 중에 있으며, 이동폐색 및 열차간격의 효율적인 제어를 위해서는 열차에 서 직접 열차의 이동위치와 속도를 정확하게 실시간으로 파악할 수 있어야 한다. 하지만 기존 철도시스템에서는 열차의 위치 및 속도확인을 위해 궤도회로와 타코메터를 이용하고 있으며, 효율적인 열차제어를 위해 지상설비의 도움없이 안전하고 정확한 열차위치정보의 확보가 필요하다. 따라서 본 논문에서는 위성항법수신기, 관성센서, 도플러레이더센서, 타코메터와 같이 열차에 탑재 가능한 위치 및 속도센서를 통합 적용하여 단독으로 열차 위치 및 속도파악이 가능한 차상기반 열차위치검지 장치를 구성하고, 한국형 틸팅열차 탑재시험을 통해 위치정확성을 평가하고 철도운영 환경에서의 적용성을 확인한다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1629_1630
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• 2009

유비쿼터스 교통 환경에서 GNSS 전파 수신 신호 상태와 상관없이 차량의 위치 정보 및 차량의 돌발 상황에 대한 서비스를 제공하기 위한 관성 항법 장치의 개발에 대해 소개한다. 제안된 시스템은 위치 파악에 많은 오차를 유발시키는 고도 부분을 분리하였고, GNSS 신호 유무에 상관없이 동작할 수 있는 시스템을 제안하였다. IMU에서는 100Hz의 속도로 위치를 파악하며, 움직이는 차량의 위치를 120초 이내에서는 GNSS 전파 수신하는 환경과 유사한 위치 오차 내에서 동작이 가능함을 실험을 통해 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.34-39
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• 1993

Presented in this paper is a complete error covariance analysis for strapdown inertial navigation system(SDINS). We have found that in SDINS the cross-coupling terms in gyrocompass alignment errors can significantly influence the SDINS error propagation. Initial heading error has a close correlation with the east component of gyro bias erro, while initial level tilt errors are closely related to accelerometer bias errors. In addition, pseudo-state variables are introduced in covariance analysis for SDINS utilizing the characteristics of gyrocompass alignment errors. This approach simplifies the covariance analysis because it makes the initial error covariance matrix to a diagonal form. Thus a real implementation becomes easier. The approach is conformed by comparing the results for a simplified case with the covariance analysis obtained from the conventional SDINS error model.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.299-303
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• 1993

In an underwater vehicle, the navigation error is mostly caused by the initial misalignment, the bias of a gyro and an accelerometer, and the sea current. Therefore, it is important that these error sources are estimated and compensated in order to reduce the navigation error. In this paper, the E.M.Log aided SDINS is designed by using the E.M.Log which measures the forward velocity of a vehicle. And the system error state equation and the measurement equation are derived and the suboptimal Kalman Filter is established for this aided SDINS. The simulation result showed that this had an important role in estimating and compensating these error sources, thus reducing the navigation error of an underwater vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.142-146
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• 1991

In order to develope transfer alignment algorithm which achieves accurate initial alignment of slave strapdown inertial navigation system(SDINS) of a missle using master SDINS of mobile launchers third-order suboptimal filter is constructed to estimate the transformation matrix between two SDINS coordinates. In Kalman Filter formulation, the measurement equation uses that of accelerometer when stationary, and is replaced by that of gyroscope when elevating the missle. This switching method is applied to increase the degree of observability and to remove the error generated by lever arm effect. Simulation results show that the azimuth transfer error is about 0.3 mrad, and confirm that this scheme has a potential for real application.