• International Journal of Aeronautical and Space Sciences
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• 제6권1호
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• pp.27-43
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• 2005

An INS(Inertial Navigation System) is composed of a navigation computer and an IMU(Inertial Measurement Unit), and can be applied to estimate a vehicle's state. But the inertial sensors assembled in the IMU are too complicated and expensive to use for the general application purpose. In this study, a new concept of inertial sensor system using magnetic levitation is proposed. The proposed system is expected to replace one single-axis rate or position gyroscope, and one single-axis accelerometer concurrently with a relatively simple structure. A simulation of the proposed system is given to describe the capability of this new concept.

• Annals of Rehabilitation Medicine
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• 제42권6호
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• pp.872-883
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• 2018

Objective To replace camera-based three-dimensional motion analyzers which are widely used to analyze body movements and gait but are also costly and require a large dedicated space, this study evaluates the validity and reliability of inertial measurement unit (IMU)-based systems by analyzing their spatio-temporal and kinematic measurement parameters. Methods The investigation was conducted in three separate hospitals with three healthy participants. IMUs were attached to the abdomen as well as the thigh, shank, and foot of both legs of each participant. Each participant then completed a 10-m gait course 10 times. During each gait cycle, the hips, knees, and ankle joints were observed from the sagittal, frontal, and transverse planes. The experiments were conducted with both a camera-based system and an IMU-based system. The measured gait analysis data were evaluated for validity and reliability using root mean square error (RMSE) and intraclass correlation coefficient (ICC) analyses. Results The differences between the RMSE values of the two systems determined through kinematic parameters ranged from a minimum of 1.83 to a maximum of 3.98 with a tolerance close to 1%. The results of this study also confirmed the reliability of the IMU-based system, and all of the variables showed a statistically high ICC. Conclusion These results confirmed that IMU-based systems can reliably replace camera-based systems for clinical body motion and gait analyses.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2022년도 제66차 하계학술대회논문집 30권2호
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• pp.491-492
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• 2022

본 연구에서는 실내 공간 정보 획득을 위한 IMU/INS 항법장치에 관한 연구를 위한 선행연구를 수행 하였다. 최근의 GPS를 이용한 내비게이션의 경우 보통 5~10m의 위치 오차가 일어나지만 아파트나 대형시설과 같이 실내, 터널, 공장지대 및 산악 지대등 상당한 지역은 GPS의 사각지대 또는 오차 범위를 벗어난 지역으로 존재하고 있다. 따라서 GPS는 실내에서는 사용이 불가능 하므로 다른 방안이 제시되어야 한다. 현재 고속 연산을 위한 고성능 마이크로프로세서의 발전은 센서 분야에 적용되어 저 전력, 고 정밀, 소형의 IMU/INS, ARS/AHRS 센서가 개발되고 있다. 본 연구에서는 IMU(inertial measurement unit)와 INS(Inertial Navigation System)을 이용하여 IMU자체의 자이로 센서와 가속도 센서를 이용한 GPS의 위성신호가 감지되지 않는 지형에서도 속도의 적분값과 회전방향을 이용하여 위치인식이 가능하도록 정보를 계산하여 자기의 위치를 추적하는 방안을 연구하였다.

• Journal of Positioning, Navigation, and Timing
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• 제9권3호
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• pp.273-284
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• 2020

The performance of Global Navigation Satellite System (GNSS) chipset and Inertial Measurement Unit (IMU) sensors embedded in smartphones for location-based services (LBS) is limited due to the economic reasons for their mass production. Therefore, it is necessary to efficiently process the output data of the smartphone's embedded sensors in order to derive the optimum navigation values and, as a previous step, output performance of smartphone embedded sensors needs to be verified. This paper analyzes the navigation performance of such devices by processing the raw measurements data output from smartphones. For this, up-to-dated versions of smartphones provided by Samsung (Galaxy s10e) and Xiaomi (Mi 8) are used in the test experiment to compare their performances and characteristics. The GNSS and IMU data are extracted and saved by using an open market application software (Geo++ RINEX Logger & Mobile MATLAB), and then analyzed in post-processing manner. For GNSS chipset, data is extracted from static environments and verified the position, Carrier-to-Noise (C/N₀), Radio Frequency Interference (RFI) performance. For IMU sensor, the validity of navigation and various location-based-services is predicted by extracting, storing and analyzing data in static and dynamic environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.3011-3024
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• 2021

Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.

• 한국항행학회논문지
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• 제25권1호
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• pp.68-77
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• 2021

본 논문에서는 높은 동특성 환경에서 동작이 가능한 GPS/MEMS IMU 통합항법 수신모듈을 설계 및 제작하고, 그 결과를 확인하였다. 설계한 모듈은 RF 수신부, 관성측정부, 신호처리부, 상관기, 항법 S/W로 구성된다. RF 수신부는 저잡음증폭, 주파수 변환, 필터링, 자동이득조절 기능을 수행하고, 관성측정부는 3축 자이로스코프, 가속도계, 지자기센서가 적용된 MEMS급 IMU로부터 측정 데이터를 수집하여 항법S/W로 전달하는 인터페이스를 제공한다. 신호처리부 및 상관기는 FPGA 로직으로 구현하여 필터링 및 상관 값 계산을 수행하고, FPGA 내부 CPU를 사용하여 위성항법, 통합항법 S/W를 구현하였다. 제작된 모듈의 크기는 95.0 × 85.0 × 12.5 mm 이고, 무게는 110g을 확인하였으며, 동적성능 1200m/s, 가속도 10g의 환경에서 규격 이내의 항법정확도 성능을 확인하였다.

• 대한인간공학회지
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• 제35권5호
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• pp.319-341
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• 2016

Objective:This research analyzed the lower-limb motion in kinetic and kinematic way while walking on various terrains to develop Foot-Ground Contact Detection (FGCD) algorithm using the Inertial Measurement Unit (IMU). Background: To estimate the location of human in GPS-denied environments, it is well known that the lower-limb kinematics based on IMU sensors, and pressure insoles are very useful. IMU is mainly used to solve the lower-limb kinematics, and pressure insole are mainly used to detect the foot-ground contacts in stance phase. However, the use of multiple sensors are not desirable in most cases. Therefore, only IMU based FGCD can be an efficient method. Method: Orientation and acceleration of lower-limb of 10 participants were measured using IMU while walking on flat ground, ascending and descending slope and stairs. And the inertial information showing significant changes at the Heel strike (HS), Full contact (FC), Heel off (HO) and Toe off (TO) was analyzed. Results: The results confirm that pitch angle, rate of pitch angle of foot and shank, and acceleration in x, z directions of the foot are useful in detecting the four different contacts in five different walking terrain. Conclusion: IMU based FGCD Algorithm considering all walking terrain possible in daily life was successfully developed based on all IMU output signals showing significant changes at the four steps of stance phase. Application: The information of the contact between foot and ground can be used for solving lower-limb kinematics to estimating an individual's location and walking speed.

• 지구물리
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• 제9권2호
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• pp.77-86
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• 2006

실시간 동적 GPS (Real-Time Kinematic Global Positioning System) 측량과 관성항법장치인 IMU(InertialMeasurement Unit)는 보다 정확한 지형정보의 획득과 동체의 모니터링에 이르기 까지 그 활용범위가 확대되어가고 있다. 실시간 동적 GPS 안에 신속히 수행할 수 있으며 , IMU는 정확하게 동적자세를 결정할 수 있기 때문에 교량 등 대형구조물의 거동을 모니터링 하는데 유용한 방법으로 대두되고 있다 . 따라서 본 연구에서는 대형구조물의 거동을 모니터링하는 시스템을 구축하기 위해서 GPS 측위방법 중 실시간 동적 GPS 측량 방법을 이용하여 현수교 주탑의 거동을 측량함에 있어, 먼저 GPS에 의한 정확한 위치를 분석하였으며 , 이를 바탕으로 실시간 동적 GPS 측량과 IMU를 이용한 모니터링 경보 시스템을 개발하였다 . 개발된 시스템으로 관측한 결과와 비교하여 , X축은 1mm, Y축은 1mm, Z축은 2.2m 로서 실시간 동적 GPS 측량과 IMU를 이용한 구조물 모니터링 측량이 가능함을 입증할 수 있었다 .

• 센서학회지
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• 제28권6호
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• pp.345-354
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• 2019

The 3D position of pedestrians is a physical quantity used in various fields, such as automotive navigation and augmented reality. An inertial navigation system (INS) based pedestrian dead reckoning (PDR), hereafter INS-PDR, estimates the relative position of pedestrians using an inertial measurement unit (IMU). Since an INS-PDR integrates the accelerometer signal twice, cumulative errors occur and cause a rapid increase in drifts. Various correction methods have been proposed to reduce drifts. For example, one of the most commonly applied correction method is the zero velocity update (ZUPT). This study investigated the characteristics of the existing INS-PDR methods based on shoe-mounted IMU and compared the estimation performances under various conditions. Four methods were chosen: (i) altitude correction (AC); (ii) step length correction (SLC); (iii) advanced heuristic drift elimination (AHDE); and (iv) magnetometer-based heading correction (MHC). Experimental results reveal that each of the correction methods shows condition-sensitive performance, that is, each method performs better under the test conditions for which the method was developed than it does under other conditions. Nevertheless, AC and AHDE performed better than the SLC and MHC overall. The AC and AHDE methods were complementary to each other, and a combination of the two methods yields better estimation performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.664-667
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• 1996

This paper presents the error parameter estimation technique for IMU(Inertial Measurement Unit) which is core sensor of INS(Inertial Navigation System) and verifies it via laboratory test. Firstly the error characteristic of gyroscope and accelerometer which is contained in IMU is examined and the error modelling is executed. The error of IMU can be divided into deterministic and random part, and the deterministic error can be divided into static and dynamic part. This paper consider the random part as constant. Secondly the error parameter estimation technique and following procedure for laboratory test is explained. Thirdly according to the test procedure the IMU test for static error is executed using 2-axis rate table and estimation result is presented with discussion about its validity.