• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.437-444
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• 2024

The rotational inertial navigation system can provide more accurate navigation information by mounting an IMU (Inertial Measurement Unit) on the gimbal and rotating the gimbal regularly to cancel out the errors of the IMU. However, when an attitude change occurs due to waves, the attitude error is not removed to 0 at the end of one cycle of the rotation procedure and causes a large position error. In this paper, considering this problem, we propose a method of stabilizing the external gimbal by rotating it based on the roll information of the vehicle. Based on simulation, the impact of waves is analyzed and the performance of external gimbal stabilization is verified.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.47-52
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• 2005

This paper describes how a relatively compensate the error of position by using low cost Inertial Measurement Unit (IMU) has been evaluated and compared with the well established method based on a Kalman Filter(KF). The compensation algorithm by using IMU have been applied to the problem of integrating information from an Inertial Navigation System (INS). The KF is to estimate and compensate the errors of an INS by using the integrated INS velocity and position. We verify the proposed algorithm by simulation results.

• The Journal of Korean Physical Therapy
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• v.29 no.3
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• pp.145-151
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• 2017

Purpose: The purpose of this study was to investigate the validity and reliability of the measurement of shoulder joint motions using an inertial measurement unit (IMU). Methods: For this study, 33 participants (32 females and 1 male) were recruited. The subjects were passively positioned with the shoulder placed at specific angles using a goniometer (shoulder flexion $0^{\circ}-170^{\circ}$, abduction $0^{\circ}-170^{\circ}$, external rotation $0^{\circ}-90^{\circ}$, and internal rotation $0^{\circ}-60^{\circ}$ angles). Kinematic data on the shoulder joints were simultaneously obtained using IMU three-dimensional (3D) angular measurement (MyoMotion) and photographic measurement. Test-retest reliability and concurrent validity were examined. Results: The MyoMotion system provided good to very good relative reliability with small standard error of measurement (SEM) and minimal detectable change (MDC) values from all three planes. It also presented acceptable validity, except for some of shoulder flexion, shoulder external rotation, and shoulder abduction. There was a trend for the shoulder joint measurements to be underestimated using the IMU 3D angular measurement system compared to the goniometer and photo methods in all planes. Conclusion: The IMU 3D angular measurement provided a reliable measurement and presented acceptable validity. However, it showed relatively low accuracy in some shoulder positions. Therefore, using the MyoMotion measurement system to assess shoulder joint angles would be recommended only with careful consideration and supervision in all situations.

• Journal of Mechanical Science and Technology
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• v.17 no.5
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• pp.629-636
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• 2003

This paper introduces the developed geometry PIG (Pipeline Inspection Gauge), one of several ILI (In-Line Inspection) tools, which provide a full picture of the pipeline from only single pass, and has compact size of the electronic device with not only low power consumption but also rapid response of sensors such as calipers, IMU and odometer. This tool is equipped with the several sensor systems. Caliper sensors measure the pipeline internal diameter, ovality and dent size and shape with high accuracy. The IMU (Inertial Measurement Unit) measures the precise trajectory of the PIG during its traverse of the pipeline. The IMU also provide three-dimensional coordination in space from measurement of inertial acceleration and angular rate. Three odometers mounted on the PIG body provide the distance moved along the line and instantaneous velocity during the PIG run. The datum measured by the sensor systems are stored in on-board solid state memory and magnetic tape devices. There is an electromagnetic transmitter at the back end of the tool, the transmitter enables the inspection operators to keep tracking the tool while it travels through the pipeline. An experiment was fulfilled in pull-rig facility and was adopted from Incheon LT (LNG Terminal) to Namdong GS (Governor Station) line, 13 km length.

• ETRI Journal
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• v.26 no.5
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• pp.497-500
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• 2004

In this paper, we present a novel idea to integrate a low cost inertial measurement unit (IMU) and Global Positioning System (GPS) for land vehicle localization. By taking advantage of positioning data calculated from an image based on photogrammetry and stereo-vision techniques, errors caused by a GPS outage for land vehicle localization were significantly reduced in the proposed bimodal approach. More specifically, positioning data from the photogrammetric approach are fed back into the Kalman filter to reduce and compensate for IMU errors and improve the performance. Experimental results are presented to show the robustness of the proposed method, which can be used to reduce positioning errors caused by a low cost IMU when a GPS signal is not available in urban areas.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.3
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• pp.234-239
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• 2010

The utilization of micro-electro-mechanical system (MEMS) gyros and accelerometers in low-level inertial measurement unit (IMU) influences cost effectiveness in a positive way under the condition that device error characteristics are fully calibrated. The conventional calibration process utilizes a rate table; however, this paper proposes a new method for achieving reference calibration data from the natural motion of pendulum to which the IMU undergoing calibration is attached. This concept was validated with experimental data. The pendulum angle measurements correlate extremely well with the solutions acquired from the pendulum equation of motion. The calibration data were computed using the regression method. The whole process was validated by comparing the measurement from the 6 sensor components with the measurements reconstructed using the identified calibration data.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.4
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• pp.285-291
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• 2015

In this paper, we propose a classification algorithm for postures of sitting person by using IMU(inertial measurement unit). This algorithm uses PCA(principle component analysis) for decreasing the number of feature vectors to three and SVM(support vector machine) with RBF(radial basis function) kernel for classifying posture types. In order to collect the data, we designed neckband-shaped earphones with IMU, and applied it to three subjects who are healthy adults. Subjects were experimented three sitting postures, which are neutral posture, smartphoning, and writing. As the result, our PCA-SVM algorithm showed 95% confidence while the dimension of the feature vectors was reduced to 25%.

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.202-207
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• 2016

Estimation of vertical position is critical in applications of sports science and fall detection and also controls of unmanned aerial vehicles and motor boats. Due to low accuracy of GPS(global positioning system) in the vertical direction, the integration of IMU(inertial measurement unit) with the GPS is not suitable for the vertical position estimation. This paper investigates an IMU-barometer integration for estimation of vertical position (as well as vertical velocity). In particular, a new two-step Kalman/complementary filter is proposed for accurate and efficient estimation using 6-axis IMU and barometer signals. The two-step filter is composed of (i) a Kalman filter that estimates vertical acceleration via tilt orientation of the sensor using the IMU signals and (ii) a complementary filter that estimates vertical position using the barometer signal and the vertical acceleration from the first step. The estimation performance was evaluated against a reference optical motion capture system. In the experimental results, the averaged estimation error of the proposed method was 19.7 cm while that of the raw barometer signal was 43.4 cm.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.143-144
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• 2016

본 논문은 보행자의 각 발에 부착된 2개의 IMU(Inertial Measurement Unit) 정보를 융합하여 위치 추적 성능을 향상시키는 보행자 추측 항법 알고리즘을 제안하였다. 센서내의 방향드리프트로 인해 IMU기반 보행자 위치추적은 시간이 지남에 따라 성능이 크게 저하된다. 제안하는 알고리즘은 방향 드리프트로 인해 각 발의 이동경로가 발산하는 점에 착안하여, 보폭이 일정 값을 초과할 시 이를 보정하고 사용자의 위치를 계산한다. 실험을 통해 제안하는 알고리즘이 방향 드리프트를 효과적으로 감소시키는 것을 확인하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.1
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• pp.36-45
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• 2017

Abstract It is necessary to verify the properties of an inertial measurement unit in the flight environment before applying to military applications. In this paper, we presented a new approach to verify an inertial measurement unit(IMU) in regard to the performance and the robustness in flight environments for the high-dynamics vehicle systems. We proposed two methods for verification of an IMU. We confirmed normal operation of an IMU and properties in flight environment by using direct comparison method. And we proposed real time multi-navigation system to complement the first method. The proposed method made it possible to compare navigation result at the same time. Therefore, it is easy to analyze the performance of an inertial navigation system and robustness during the vehicle flight. To verify the proposed method, we carried out a flight test as well as an experimental test of flight vibration on the ground. As a result of the experiment, we confirmed flight environment properties of an IMU. Therefore, we shows that the proposed method can serve the reliability improvement of IMU.