• 한국소음진동공학회논문집
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• 제26권6_spc호
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• pp.644-650
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• 2016

Track maintenance works based on track geometry recordings are essential to enhance the safety and comfort of railway transportation. Usually, the track irregularity has been measured by a special inspection trains which all were imported from abroad. Because the inspection train speed is limited under 160 km/h, it takes a long time to inspect railways and there is difficulty in daytime operation. To solve this problem, we started to develop a track geometry measuring system (TGMS) with measurement speed up to 300 km/h which can be installed in commercial vehicles such as HEMU-430X. In this paper, we introduce a newly developed inertial TGMS and propose two inertial navigation system (INS) algorithms (method A, B) for measuring track geometry. In order to investigate advantage and disadvantage of each algorithm, we performed vibration test of the TGMS, which was simulated by 6-axis shaking table. Through the vibration test, we analyzed the influence of vehicle vibration on the TGMS which will be installed on bogie frame. To the vibration test, two methods satisfied the required accuracy of track geometry measurement under the level of the actual vehicle vibration of HEMU-430X train. Theoretically, method A is sensitive to vehicle vibration than method B. However, HEMU-430X's bogie vibration frequency range is out of interest range of measurement system. Therefore, method A can also apply the HEMU-430X train.

• Advances in aircraft and spacecraft science
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• 제1권4호
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• pp.455-469
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• 2014

High-precision autonomous localization technique is essential for future Mars rovers. This paper addresses an innovative integrated localization algorithm using a multiple information fusion approach. Firstly, the output of IMU is employed to construct the two-dimensional (2-D) dynamics equation of Mars rover. Secondly, radio beacon measurement and terrain image matching are considered as external measurements and included into the navigation filter to correct the inertial basis and drift. Then, extended Kalman filtering (EKF) algorithm is designed to estimate the position state of Mars rovers and suppress the measurement noise. Finally, the localization algorithm proposed in this paper is validated by computer simulation with different parameter sets.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.87-94
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• 2013

UKF (Unscented Kalman Filter) has been used in the nonlinear systems without initial accurate state estimates instead of EKF (Extended Kalman Filter) of the last decade because the UKF has robustness to the large initial estimation error. In the multirate integrated system such as INS (Inertial Navigation System)/GPS (Global Positioning System) integrated navigation system, however, it is difficult to implement the UKF based navigation algorithm in the mid-grade micro-processor due to the large computational burden. To overcome this problem, this paper proposes a MUKF (Modified UKF) that has a reduced computation burden using the basic idea that the change of the provability distribution for the state variables between measurement updates is small in the multi-rate INS/GPS integrated navigation filter. The performance of the proposed MUKF is verified by numerical simulations.

• Journal of Positioning, Navigation, and Timing
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• 제9권1호
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• pp.33-42
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• 2020

In Integration Approach (IA)-based Pedestrian Dead Reckoning (PDR), it is important to detect the exact zero-velocity of the foot with an Inertial Measurement Unit (IMU). By detecting zero-velocity during the stance phase of the foot touching the ground and executing Zero-velocity UPdaTe (ZUPT) at the exact time, stable navigation information can be provided by the PDR. When the pace is fast, however, it is not easy to accurately detect the zero-velocity because of the small stance phase interval and the large signal variance of the corresponding interval. Incorrect zero-velcity detection greatly causes navigation errors of IA-based PDR. In this paper, we propose a method to detect the zero-velocity stably even at high speed by novel buffering of IMU's output data and signal processing of the buffer. And we design a PDR based on this. By analyzing the performance of the proposed Zero-Velocity Detection (ZVD) algorithm and ZVD-based PDR through experiemnts, we confirm that the proposed method can provide accurate navigation information of pedestrians such as firefighters in the indoor space.

• 한국ITS학회 논문지
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• 제19권1호
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• pp.94-106
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• 2020

근래의 위치 측위 방법으로 GPS(Global Positioning System) 위성정보를 활용하는 전파항법 방식을 많이 사용하고 있다. GPS 활용범위가 넓어지고 다양한 측위 정보를 기반으로 하는 분야가 생기면서 보다 높은 정확도를 얻기 위한 새로운 방법들이 요구되고 있다. 자율주행차의 경우 IMU(Inertial Measurement Unit)를 사용한 항법 시스템인 INS(Inertial Navigation System)와 차량 내부 센서를 이용한 DR(Dead Reckoning) 알고리즘을 사용하여 GPS의 정확도 저하나 음영지역에서의 위치 측정방법으로 사용하고 있다. 그러나 이러한 측위 방법은 대형화되는 빌딩 지역, 터널, 지하 주차장 등 다양한 음영지역과 시간이 지남에 따라 오차가 계속 증가하는 누적 기반 위치추정 방법의 한계로 인해 많은 문제 요소가 있다. 본 논문은 GPS 음영지역에서 차량의 위치 측위를 위해, 대중적 무선 통신인 WLAN을 이용한 Fingerprint 기법을 4개의 Anchor 형태로 AP(Access Point)와 지향성 안테나를 위치하여 넓은 지하 주차공간에서 효율적인 측위 방법을 제시하고 시간이 지남에 따라 주차된 차량이 이동하는 환경에서도 변화가 없는 위치 측위 결과를 입증하였다.

• 제어로봇시스템학회논문지
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• 제7권1호
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• pp.1231-1239
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• 2001

This paper presents a new leveling algorithm that estimates the initial horizontal angles composed of roll angle and pitch angle for a moving or stationary vehicle. The system model of the EKF is designed by linearizing the nonlinear Euler angle differential equation. The measurement models are designed for the moving case and for the stationary case, respectively. The simulation results show that the leveling algorithm is ade-quate not only for acquiring the initial horizontal angles of the vehicle in the motion with acceleration and rotation but also for the stationary one.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.238-243
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• 1997

A new transfer alignment algorithm using the velocity and the quaternion partial matching methods is proposed to reduce the effect of a ship's Y-axis flexure on the performance of azimuth error estimation of Kalman filter. The simulation results show that it can significantly reduce the effect of Y-axis flexure on error estimation by the transfer alignment algorithm. As its results, azimuth transfer alignment error is reached up to 3 mrad under proper roll and pitch attitude motion of the ship.

• International Journal of Aeronautical and Space Sciences
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• 제2권1호
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• pp.55-66
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• 2001

The Global Positioning System(GPS) and the Strapdown Inertial Navigation System(SDINS) techniques have been widely utilized in many applications. However each system has its own weak point when used in a stand-alone mode. SDINS suffers from fast error accumulation dependent on an operating time while GPS has problem of cycle slips and just provides low update rate. The best solution is to integrate the GPS and SDINS system and its integration allows compensation for each shortcomings. This paper, first, is to define and derive error equations of integrated SDINS/GPS system before it will be applied on a real hardware system with gyro, accelerometer and GPS receiver. Second, the accuracy, availability and performance of this mechanization are verified on the simulation study.

• Journal of Positioning, Navigation, and Timing
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• 제12권1호
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• pp.37-42
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• 2023

Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.

• International Journal of Naval Architecture and Ocean Engineering
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• 제11권2호
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• pp.679-687
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• 2019

This paper presents the autonomous swimming technology developed for an Autonomous Underwater Vehicle (AUV) operating in the underwater jacket structure environment. To prevent the position divergence of the inertial navigation system constructed for the primary navigation solution for the vehicle, we've developed kinds of marker-recognition based underwater localization methods using both of optical and acoustic cameras. However, these two methods all require the artificial markers to be located near to the cameras mounted on the vehicle. Therefore, in the case of the vehicle far away from the structure where the markers are usually mounted on, we may need alternative position-aiding solution to guarantee the navigation accuracy. For this purpose, we develop a sonar image processing based underwater localization method using a Forward Looking Sonar (FLS) mounted in front of the vehicle. The primary purpose of this FLS is to detect the obstacles in front of the vehicle. According to the detected obstacle(s), we apply an Occupancy Grid Map (OGM) based path planning algorithm to derive an obstacle collision-free reference path. Experimental studies are carried out in the water tank and also in the Pohang Yeongilman port sea environment to demonstrate the effectiveness of the proposed autonomous swimming technology.