• 제목/요약/키워드: 거리 추정

검색결과 1,618건 처리시간 0.032초

집적 영상의 복원과 통계적 패턴분석을 이용한 왜곡에 강인한 3차원 물체 인식 (Three-dimensional Distortion-tolerant Object Recognition using Computational Integral Imaging and Statistical Pattern Analysis)

  • 염석원;이동수;손정영;김신환
    • 한국통신학회논문지
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    • 제34권10B호
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    • pp.1111-1116
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    • 2009
  • 본 논문에서는 집적 영상의 획득과 복원을 이용하여 왜곡에 강인한 물체를 인식하는 방법을 연구한다. 해당 화소들의 확률적 특성인 평균과 표준편차를 이용하여 3차원 공간에서 물체를 복원하고 거리를 추정한다. 표적인식은 Fisher 선형판별법(linear discriminant analysis, LDA)과 주성분 분석법(principal component analysis, PCA) 기술을 결합한 통계적 분류기(statistical classifier)로 수행한다. Fisher 선형판별법은 클래스 간의 판별력을 최대로 하고 주성분 분석법은 Fisher 선형판별법을 수행하기 위한 차원축소를 실행한다. 주성분 분석법은 차원축소 후 복원된 벡터와 원 벡터의 오차를 최소화하는 기술로 알려져 있다. 실험 및 시뮬레이션을 통하여 면외(out-of-plane) 회전된 표적을 본 논문에서 제안한 방법으로 분류한다.

클럭 표류 영향을 고려한 양방향 거리 인지 기반의 TOA/TDOA 추정 방안 (TOA/TDOA Estimation Method Based on Two Way Ranging with Considering Clock Drift Effect)

  • 박운용;박철웅;최성수;이원철
    • 한국통신학회논문지
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    • 제32권7C호
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    • pp.608-615
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    • 2007
  • 일반적으로 양방향 전송을 통한 TOA(Time Of Arrival) 정보는 두 디바이스간의 정확한 RTT(Round Trip Time) 정보로부터 도출되지만 디바이스간의 서로 다른 클럭 표류의 영향으로 인하여 RTT 측정 시 요구되는 응답 시간이 길 경우 매우 심각한 TOA 오차를 야기 시키게 된다. 이를 해결하기 위해서 본 논문에서는 비동기 시스템에서 클럭 표류의 영향을 줄이면서 TOA와 TDOA(Time Difference Of Arrival) 정보를 획득하는 방안을 제안한다. 이를 검증하기 위해서 IEEE 802.15.4a Task Group에서 제시한 단방향 전송을 통한 측위 방안과 비교하였으며 제안된 방안이 기존 방법들보다 개선된 성능을 보임을 확인하였다.

초동 전파시간과 진앙거리의 경험적인 관계를 이용한 진앙 추정 (Estimation of epicenter using an empirical relationship between epicentral distance and traveltime of the first arrival)

  • 신동훈;박창업;황의홍;전영수
    • 한국지구물리탐사학회:학술대회논문집
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    • 한국지구물리탐사학회 2007년도 공동학술대회 논문집
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    • pp.64-68
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    • 2007
  • The classic graphical method to determine the epicenter uses differences between the arrival times of P and S waves at each station. In this research, a robust approach is proposed, which provides a fast and intuitive estimation of earthquake epicenters. This method uses an empirical relationship between epicentral distance and traveltime of the first arrival P phase of local or regional earthquake. The relationship enables us to estimate epicentral distances and draw epicentral circles from each station with P-traveltimes counted from a probable origin time. As the assigned time is getting close to the origin time of the earthquake, epicentral circles begin to intersect each other at a possible location of the epicenter. Then the possibility of the epicenter can be expressed by a function of the time and the space. We choose the location which gives the minimum standard deviation of the origin time as an estimated epicenter. In this research, 918 P arrival times from 84 events occurring from 2005 to 2006 listed in the KMA earthquake catalog are used to determine the empirical P-traveltime function of epicentral distances.

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수중로봇 위치추정을 위한 베이시안 필터 방법의 실현과 거리 측정 특성 분석 (Implementation of Bayesian Filter Method and Range Measurement Analysis for Underwater Robot Localization)

  • 노성우;고낙용;김태균
    • 로봇학회논문지
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    • 제9권1호
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    • pp.28-38
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    • 2014
  • This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(Monte Carlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty is not yet proved. Along with localization, the experiment also discloses the uncertainty features of the range measurement such as bias and variance. The proposed localization method rejects outlier range data and the experiment shows that outlier rejection improves localization performance. It is as expected that the proposed method doesn't yield as precise location as those methods which use high priced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy range sensors. However, it is noticeable that the proposed method can achieve the accuracy which is affordable for correction of accumulated dead reckoning error, even though it uses only range data of low reliability and accuracy.

목표물의 거리 및 특징점 불확실성 추정을 통한 매니퓰레이터의 영상기반 비주얼 서보잉 (Image-based Visual Servoing Through Range and Feature Point Uncertainty Estimation of a Target for a Manipulator)

  • 이상협;정성찬;홍영대;좌동경
    • 제어로봇시스템학회논문지
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    • 제22권6호
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    • pp.403-410
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    • 2016
  • This paper proposes a robust image-based visual servoing scheme using a nonlinear observer for a monocular eye-in-hand manipulator. The proposed control method is divided into a range estimation phase and a target-tracking phase. In the range estimation phase, the range from the camera to the target is estimated under the non-moving target condition to solve the uncertainty of an interaction matrix. Then, in the target-tracking phase, the feature point uncertainty caused by the unknown motion of the target is estimated and feature point errors converge sufficiently near to zero through compensation for the feature point uncertainty.

노치응력법에 의한 용접 연결부 피로수명 추정에 관한 연구 (Estimation Fatigue Life of Weldments by Notch Stress Approaches)

  • 양박달치;송준규
    • 한국해양공학회지
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    • 제25권5호
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    • pp.47-51
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    • 2011
  • This paper analyzes the fatigue-life of welded joints using the notch stress approach. In the notch stress approach, the notch effects are usually approximated by introducing weld-bead parameters for the local detailed weld joints. The actual bead shape is complex and 3-dimensional. It may also greatly influence the fatigue strength. In this study, the welded shape was modeled using a 3D-scanner. The critical distance method was adopted in the evaluation of the fatigue effective notch stress for the weldments. Fatigue life tests were performed to verify the present method of fatigue life estimation for two types of welded plates with longitudinal attachments. The estimated results of the present methods were applied to the results of the experiment. The results of the analysis showed that the scatter of fatigue-life for the experimental data expressed in the nominal stress was significantly reduced by applying the effective fatigue stress of the present study.

칼만추정과 초월함수 사영을 통한 L1 신호간의 거리 Metric에 IES을 적용한 새로운 고장진단 기법 (A New Fault Diagnosis Scheme between L1 Signals Using IES on the Metric Defined via Kalman Filter and Exponential Function Transformation)

  • 김성수
    • 전기학회논문지P
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    • 제64권1호
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    • pp.23-28
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    • 2015
  • Measuring the distances between signals in the signal space is usually determined by obtaining the ideal metric which is not easy to obtain. In this research we have investigated the scheme that measures the distances between the signals constructed with the measured voltage signals connected to electric apparatus using Kalman filter and exponential mapping. The metric is defined on the feature signals obtained via the estimation process of a Kalman filter and the mapping process using the exponential transformation. Diagnosis is on the voltage fluctuations is applied to determining whether the system is in the stable state or not due to the unexpected accidents, such as power overcharge, discharge, outages flow may be the cause of the accident. The decision making scheme evaluated with respect to the effectiveness and the degree of complication with different variances. Two methods, the Hard Limit Threshold Scheme(HLTS) and the Interval Energy Scheme(IES) are proposed and compared. In experiments the IES shows better tolerance to impulse noise than the HLTS.

고속 적응자동재폐로를 위한 사고거리추정 및 사고판별에 관한 개선된 양단자 수치해석 알고리즘 (An Improved Two-Terminal Numerical Algorithm of Fault Location Estimation and Arcing Fault Detection for Adaptive AutoReclosure)

  • 이찬주;김현홍;박종배;신중린;조란 라도예빅
    • 대한전기학회논문지:전력기술부문A
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    • 제54권11호
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    • pp.525-532
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    • 2005
  • This paper presents a new two-terminal numerical algorithm for fault location estimation and for faults recognition using the synchronized phaser in time-domain. The proposed algorithm is also based on the synchronized voltage and current phasor measured from the assumed PMUs(Phasor Measurement Units) installed at both ends of the transmission lines. Also the arc voltage wave shape is modeled numerically on the basis of a great number of arc voltage records obtained by transient recorder. From the calculated arc voltage amplitude it can make a decision whether the fault is permanent or transient. In this paper the algorithm is given and estimated using DFT(discrete Fourier Transform) and the LES(Least Error Squares Method). The algorithm uses a very short data window and enables fast fault detection and classification for real-time transmission line protection. To test the validity of the proposed algorithm, the Electro-Magnetic Transient Program(EMTP/ATP) is used.

병행 2회선 송전선로에서 고장점 위치 추정정보를 이용한 실시간 거리계전 알고리즘 (The Real-Time Distance Relay Algorithm Using fault Location Estimation Information for Parallel Transmission Line)

  • 이재규;유석구
    • 대한전기학회논문지:전력기술부문A
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    • 제52권3호
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    • pp.183-192
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    • 2003
  • This paper presents the real-time implemented distance relay algorithm which the fault distance is estimated with only local terminal information. When a single-phase-to-earth fault on a two-parallel transmission line occurs, the reach accuracy of distance relay is considerably affected by the unknown variables which are fault resistance, fault current at the fault point and zero- sequence current of sound line The zero-sequence current of sound line is estimated by using the zero sequence voltage which is measured by relaying location Also. the fault resistance is removed at the Process of numerical formula expansion. Lastly, the fault current through a fault point is expressed as a function of the zero-sequence current of fault line, zero-sequence current of sound line, and line, and fault distance. Therefore, the fault phase voltage can be expressed as the quadratic equation of the fault distance. The solution of this Quadratic equation is obtained by using a coefficient of the modified quadratic equation instead of using the square root solution method. After tile accurate fault distance is estimated. the mote accurate impedance is measured by using such an information.

계층적 클러스터링과 Gaussian Mixture Model을 이용한 뉴로-퍼지 모델링 (A Neuro-Fuzzy Modeling using the Hierarchical Clustering and Gaussian Mixture Model)

  • 김승석;곽근창;유정웅;전명근
    • 한국지능시스템학회논문지
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    • 제13권5호
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    • pp.512-519
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    • 2003
  • 본 논문에서는 계층적 클러스터링과 GMM을 순차적으로 이용하여 최적의 파라미터를 추정하고 이를 뉴로-퍼지 모델의 초기 파리미터로 사용하여 모델의 성능 개선을 제안한다. 반복적인 시도 중 가장 좋은 파라미터를 선택하는 기존의 알고리즘 과 달리 계층적 클러스터링은 데이터들 간의 유클리디언 거리를 이용하여 클러스터를 생성하므로 반복적인 시도가 불필요하다. 또한 클러스터링 방법에 의해 퍼지 모델링을 행하므로 클러스터와 동일한 갯수의 적은 규칙을 갖는다. 제안된 방법의 유용함을 비선형 데이터인 Box-Jenkins의 가스로 예측 문제와 Sugeno의 비선형 시스템에 적용하여 이전의 연구보다 적은 규칙으로도 성능이 개선되는 것을 보였다.