시변 자기 환경에 강한 자기왜곡 모델 내장형 헤딩 추정 필터

이정근,최미진,Lee, Jung Keun,Choi, Mi Jin 한국센서학회 2017 센서학회지 Vol.26 No.4

With regards to heading estimation using gyroscope and magnetometer signals, magnetic disturbance added in the magnetometer signals is a main degradation factor in the estimation accuracy. Although there are a number of existing mechanisms that may properly compensate for the magnetic disturbances, they are designed to react only to the magnetic disturbances, but not to the time derivative of disturbances. Note that the sensors may experience abrupt changes in the magnetic disturbances, particularly for ambulatory applications. This paper proposes a magnetic disturbance model-embedded heading estimation filter for time-varying magnetic environments. The proposed magnetic disturbance model is based on a first-order Markov chain with a conditional switching technique depending on the time derivative of disturbances. Once a high amount of derivative is detected, the corrupted magnetometer signals are discarded to protect the filter from them. In our experimental results, the averaged heading error of tests was $1.46^{\circ}$, while that of the original approach without switching was $5.75^{\circ}$.

비정렬과 약성 왜곡을 고려한 타원체 피팅 방식 지자기 센서 캘리브레이션

이정근(Jung Keun Lee),전태형(Tae Hyeong Jeon) 제어로봇시스템학회 2017 제어·로봇·시스템학회 논문지 Vol.23 No.12

The calibration of magnetometers is essential for achieving accurate heading estimations as magnetometer signals can often be corrupted due to various types of magnetic distortions such as offset, sensitivity, hard-iron distortion, misalignment, and soft-iron distortion. In literature, most calibration methods have focused on the former three distortions, while the latter two have received little attention in spite of their importance. This paper proposes a novel ellipsoid-fitting magnetometer calibration method that considers misalignment and soft-iron distortion. A complete calibration model with 24 parameters is established based on an ellipsoid restriction and experimental results show that the proposed method outperformed two other ellipsoid-fitting calibration methods in terms of the root mean squared errors of heading estimations under two different distorted conditions.

사무공간의 등기구 적용에 따른 책상면 조도 비교 평가분석

이정근(Jung-Geun Lee),이민진(Min-Jin Lee),정희석(Hee-Suk Jeong),황명근(Myung-Keun Hwang) 한국조명·전기설비학회 2012 한국조명·전기설비학회 학술대회논문집 Vol.2012 No.5

IMU기반 자세결정의 정확도 향상을 위한 가속도 보상 메카니즘 비교

이정근(Jung Keun Lee) 대한기계학회 2016 大韓機械學會論文集A Vol.40 No.9

IMU기반 자세결정에 있어 추정 정확도의 저하요인 중 주요한 한 가지는 운동체의 가속도이다. 이는 가속도가 크게 발생하는 경우 가속도계 신호는 더이상 수직축 참조벡터가 될 수 없기 때문이다. 이에 대한 대책으로 일부 자세추정 알고리즘에서는 가속도 보상 메카니즘이 적용되어 왔다. 가장 보편적이고 간단한 스위칭 방법부터 적응추정방식, 가속도 모델기반 방식 등이 제안되어 왔으나, 이들 보상 메카니즘에 대한 비교분석은 이루어 지지 않았다. 본 논문은 쿼터니언기반의 Pseudo 칼만필터를 바탕으로 하여 세 가지 가속도 보상 메커니즘의 성능을 비교분석하였다. 가속조건 실험 분석을 통해 다음을 확인할 수 있었다. (1) 가속구간에서의 추정정확도 저하를 방지하기 위해선 가속도 보상 메카니즘이 반드시 필요하다. (2) 단순 스위칭 방법도 상당한 효과를 보였으나, 보다 정교한 적응추정 방식과 가속도 모델방식이 동등수준으로 가장 정확한 결과를 보였다. One of the main factors related to the deterioration of estimation accuracy in inertial measurement unit (IMU)-based orientation determination is the object"s acceleration. This is because accelerometer signals under accelerated motion conditions cannot be longer reference vectors along the vertical axis. In order to deal with this issue, some orientation estimation algorithms adopt acceleration-compensating mechanisms. Such mechanisms include the simple switching techniques, mechanisms with adaptive estimation of acceleration, and acceleration model-based mechanisms. This paper compares these three mechanisms in terms of estimation accuracy. From experimental results under accelerated dynamic conditions, the following can be concluded. (1) A compensating mechanism is essential for an estimation algorithm to maintain accuracy under accelerated conditions. (2) Although the simple switching mechanism is effective to some extent, the other two mechanisms showed much higher accuracies, particularly when test conditions were severe.

서포트벡터머신을 이용한 충격전 낙상방향 판별

이정근 ( Jung Keun Lee ) 한국센서학회 2015 센서학회지 Vol.24 No.1

Fall-related injuries in elderly people are a major health care problem. This paper introduces determination of fall direction before impact using support vector machine (SVM). Once a falling phase is detected, dynamic characteristic parameters measured by the accelerometer and gyroscope and then processed by a Kalman filter are used in the SVM to determine the fall directions, i.e., forward (F), backward (B), rightward (R), and leftward (L). This paper compares the determination sensitivities according to the selected parameters for the SVM (velocities, tilt angles, vs. accelerations) and sensor attachment locations (waist vs. chest) with regards to the binary classification (i.e., F vs. B and R vs. L) and the multi-class classification (i.e., F, B, R, vs. L). Based on the velocity of waist which was superior to other parameters, the SVM in the binary case achieved 100% sensitivities for both F vs. B and R vs. L, while the SVM in the multi-class case achieved the sensitivities of F 93.8%, B 91.3%, R 62.3%, and L 63.6%.

IMU-바로미터 기반의 수직변위 추정용 이단계 칼만/상보 필터

이정근 ( Jung Keun Lee ) 한국센서학회 2016 센서학회지 Vol.25 No.3

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.

자기 왜곡에 의해 야기되는 방향각 추정 불확실성을 감소시키기 위한 구속형 AHRS 칼만 필터

이정근(Jung Keun Lee),전태형(Tae Hyeong Jeon) 제어로봇시스템학회 2018 제어·로봇·시스템학회 논문지 Vol.24 No.5

An attitude and heading reference system (AHRS) based on inertial and magnetic measurement unit (IMMU) signals has a critical problem, in that the heading estimation accuracy can be degraded by magnetic distortion-induced uncertainty related to magnetometer signals. Although several distortion compensation mechanisms have been developed to deal with this issue and they showed improvement to some extent, they have an inherent limitation in that magnetic distortion-induced uncertainty is inevitable in many environments. This paper proposes a constrained AHRS Kalman filter (KF) to reduce magnetic distortioninduced uncertainty in heading estimation by exploiting the acceleration-level kinematic constraint of a spherical joint. In particular, this paper focuses on a two-link system that is connected by a spherical joint, where one link is exposed to magnetic distortions and the other link is not. The proposed KF improves the heading estimation of the former link using constraint projection. Our experimental results showed the superiority of the proposed KF to conventional unconstrained KF: The root mean square errors of the heading estimation with the proposed KF were 0.75° in Test 1 and 1.85° in Test 2, while those from the conventional KF were 3.50° in Test 1 and 10.73° in Test 2.

인공신경망을 이용한 방전전하량 추정에 관한 연구

이정근(Jung-Keun Lee),송재우(Jae-Woo Song) 산업기술교육훈련학회 2011 산업기술연구논문지 (JITR) Vol.16 No.3

The paper used to the Neral Network for a forcasting conservation system. A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform “intelligent” tasks similar to those performed by the human brain. The true power and advantage of neural networks lies in their ability to represent both linear and non-linear relationships and in their ability to learn these relationships directly from the data being modeled. Form results of this study, the Neral Network is will play an important role for insulation diagnosis system of real site GIS and power equipment using Imitation-Air.

IPTV 양방향성 콘텐츠의 미디어 수용의사와 만족도 상관관계 연구

이정근(Lee Jung-keun),정진도(Chung Jin-Do) 한국컴퓨터정보학회 2008 韓國컴퓨터情報學會論文誌 Vol.13 No.1

본 연구는 IPTV 사용자의 수용의사와 만족도에 양방향성 콘텐츠가 미치는 영향을 7가지 변수를 중심으로 조사하였다. 내용적인 측면에서는 오락성, 개인화, 최신성, 정보성을, 시스템적 측면에서는 안정성, 사용편리성, 반응속도로 구성하였다. 이의 요인들이 수용의사와 만족도에 미치는 상관관계를 실증 분석했다. 조사 결과 첫째, 양방향성 콘텐츠가 미디어 수용의사에 유의한 영향을 미치는 변수로는 오락성과 정보성의 순으로 나타났으며, 양방향성 콘텐츠의 시스템적인 측면보다는 내용적 측면이 수용의사와 깊은 관련성이 있었으며, 그 중에서도 오락성과 정보성이 높을수록 소비자의 미디어 수용의사가 향상된다는 것으로 밝혀졌다. 둘째, 양방향성 콘텐츠의 오락성, 개인화, 정보성, 안정성, 사용 편리성, 반응 속도가 높을수록 소비자의 미디어 만족도는 향상되는 것으로 나타났다. 이 중 사용편리성이 미디어 만족도에 가장 큰 영향을 미치는 것으로 밝혀졌다. This study was surveyed by using seven variables with two stems of contents-wise aspect and systematic aspect. entertainment, user-oriented contents supply, data up data, useful information supply are the elements of contents-wise aspect and systematic stabilization, convenience of access, promptness of response are for systematic aspect. Results : First, entertainment is the first variable of interactive contents for user to choose IPTV and useful information supply is the second. Also contents wise aspect is more related than the other. Second, The high quality of entertainment, user-oriented contents supply, useful information supply, systematic stabilization, convenience of access, promptness of response are required to enhance the satisfaction of IPTV user. Among them, convenience of access is the most valuable factor for user to choose IPTV.

좌표변환 기반의 두 자세 정렬 기법 비교

이정근 ( Jung-keun Lee ),정우창 ( Woo-chang Jung ) 한국센서학회 2019 센서학회지 Vol.28 No.1

Inertial measurement units (IMUs) are widely used for wearable motion-capturing systems in the fields of biomechanics and robotics. When the IMUs are combined with optical motion sensors (hereafter, OPTs) for their complementary capabilities, it is necessary to align the coordinate system orientations between the IMU and OPT. In this study, we compare the application of two coordinate transformation- based orientation alignment methods between two coordinate systems. The first method (M1) applies angular velocity coordinate transformation, while the other method (M2) applies gyroscopic angle coordinate transformation. In M1 and M2, the angular velocities and angles, respectively, are acquired during random movement for a least-square algorithm to determine the alignment matrix between the two coordinate systems. The performance of each method is evaluated under various conditions according to the type of motion during measurement, number of data points, amount of noise, and the alignment matrix. The results show that M1 is free from drift errors, while drift errors are present in most cases where M2 is applied. Thus, this study indicates that M1 has a far superior performance than M2 for the alignment of IMU and OPT coordinate systems for motion analysis.