• 제목/요약/키워드: Estimation of Distance

검색결과 1,192건 처리시간 0.037초

교통카드데이터를 활용한 하차정류장 추정 방법론 연구 (Public Transportation Alighting Estimation Method Using Smart Card Data)

  • 김경태;이인묵
    • 한국철도학회논문집
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    • 제20권5호
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    • pp.692-702
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    • 2017
  • 최근 데이터 중심적 교통정책수립 필요성 인식에 따라 교통카드데이터 활용에 관심이 고조되고 있다. 하지만 수도권 외의 많은 지역의 데이터에 하차 정보가 없어 활용에 제약이 있다. 이 논문은 승차 정보만 포함된 교통카드데이터에서 하차 정류장을 추정하는 방법론을 제시하였다. 검증은 서울시와 광주시의 데이터를 활용하였다. 추정 성공률은 서울시, 광주시 각각 78.2%, 81.6%로 나타났다. 정확도는 각각 54.2%, 33.4%로 나타났는데, 2개 정류장 오차까지 허용하는 경우 정확도가 서울시 93.6%, 광주시 94.0%로 크게 높아진다. 또한 광주시와 서울시가 오차 양상이 다름을 밝혔다. 통행사슬 방법의 핵심 매개변수인 허용 도보거리 조정에 따른 추정 성공률 및 정확도의 변화도 다루었다. 허용 도보거리가 증가됨에 따라 추정 성공률은 높아지는 반면 추정 정확도는 낮아지는 것을 확인하였으며, 500m를 전후하여 추정 결과의 변화 양상이 있음을 발견하였다.

선형마이크로폰 어레이를 이용한 저격수 거리추정 개선방법과 실험 분석 (Improvement Method and Experiment Analysis of Sniper Distance Estimation Using Linear Microphone Array)

  • 정승우
    • 한국군사과학기술학회지
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    • 제21권4호
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    • pp.447-455
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    • 2018
  • If a hidden enemy is shooting, there is a threat against soldiers in recent conflicts. This paper aims to improve the localization of a muzzle using microphone array. Gunshot noise can provide information about the location of muzzle with two signals, the muzzle blast from the gun barrel and the projectile sound from the bullet. Two signals arrive to the microphone array with different arrival time and angle. If the arrival angles of the two signals are estimated, distance between sniper location and the microphone array can be calculated by using geometric principles. This method was established in 2003 by Pare. But this method has a limitation that it cannot calculate the distance when the arrival angles of the two signals are same. Also it has an error when the angle difference of arrival is small. In order to overcome this limitation, a new method is proposed that uses the change of characteristic of the projectile sound with respect to vertical distance from the trajectory. The proposed method estimates the distance correctly when the arrival angle of two signals are same, and when the angle difference between two signals is increased, the estimation error increases with respect to the angle. Therefore these two methods can be selected according to the angle difference between two signals to estimate the distance of the muzzle. Below the threshold of the angle difference, the proposed method can be used to estimate distance with smaller error than the existing method. This was demonstrated by shooting tests using actual sniper rifles.

초음파 센서를 이용한 거리 기반 인증 시스템의 설계 및 분석 (Design and Analysis of an Authentication System based on Distance Estimation using Ultrasonic Sensors)

  • 박진오;이문규;임철수
    • 한국정보과학회논문지:시스템및이론
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    • 제36권2호
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    • pp.94-101
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    • 2009
  • 본 논문에서는 거리 확인 및 공유 키 기반의 challenge-response를 통하여 사용자를 인증하는 인증 시스템을 제안한다. 인증장치는 전파와 초음파 신호의 도달시간의 차를 이용하여 사용자가 소유한 인중토큰이 유효 거리 이내에 있는지 확인하는 동시에, 인증장치가 송신한 challenge에 대해 인증토큰이 키를 기반으로 정확한 응답을 보내는지를 확인한다. 본 논문에서는 이와 같은 인증시스템을 실제로 구현하고 인증장치와 인증토큰의 초음파 센서 방향과 위치의 변화에 따른 인증 성공률을 분석하였다. 실험 결과에 따르면 인증장치와 인증토큰의 방향이 크게 어긋나 있지 않은 상황에서는 대부분 100%에 가까운 인증 성공률을 보임을 확인할 수 있었다.

스테레오 비전에서 향상된 적응형 퍼지 칼만 필터를 이용한 거리 추정 기법 (Distance Estimation Method using Enhanced Adaptive Fuzzy Strong Tracking Kalman Filter Based on Stereo Vision)

  • 임영철;이충희;권순;이종훈
    • 전자공학회논문지SC
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    • 제45권6호
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    • pp.108-116
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    • 2008
  • 본 논문에서는 스테레오 비전에서 시차를 이용하여 근거리뿐만 아니라 원거리의 장애 물체에 대해서도 신뢰성 있는 거리를 추정하기 위한 알고리즘을 제안한다. 시차를 이용한 거리 측정에서 양자화 오차는 원거리에서의 거리 정확도를 떨어뜨리게 되므로, 이를 최소화하기 위해 부화소 보간법(sub-pixel interpolation)을 이용하여 시차 정확도를 향상시키고 거리 정확도 및 경로 추적의 최적화를 위해서 향상된 적응형 퍼지 칼만 필터(EAFSTKF : Enhanced Adaptive Fuzzy Strong Tracking Kalman Filter)를 사용한다. 제안한 방법은 차량과 같이 다양한 동적인 움직임에 의한 비선형성에 대하여 기존 칼만 필터에서 발생되는 발산 문제(divergence problem)를 해결할 수 있고, 거리의 정확도 및 신뢰도도 높일 수 있다. 몬테카를로(Monte Carlo) 방법을 이용한 모의실험 결과 제안한 방법은 기존 방법들과 거리 오차율(RMSER : Root Mean Square Error Rate)을 비교하였을 때, strong tracking Kalman filter(STKF)에 비하여 성능이 약 13.5%정도 향상되었음을 보여준다.

Robust hausdorff 거리 척도를 이용한 물체 정합 알고리듬 (Object matching algorithms using robust hausdorff distance measure)

  • 권오규;심동규;박래홍
    • 전자공학회논문지S
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    • 제34S권11호
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    • pp.93-101
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    • 1997
  • A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper proposes three object matching algorithm using robust HD measures based on M-estimation, least trimmed square (LTS), and .alpha.-trimmed mean methods, which are more efficient than the conventional HD measures. By computer simulation with synthetic and real images, the matching performance of the conventional HD smeasures and proposed' robust ones is compared.

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칼만필터링에 의한 디지털 거리계전 기법에 관한 연구 (A Study on the Digital Distance Relaying Techniques Using Kalman Filtering)

  • 김철환;박남옥;신명철
    • 대한전기학회논문지
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    • 제41권3호
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    • pp.219-226
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    • 1992
  • In this study, Kalman filtering theory is applied to the estimation of symmetrical components from fault voltage and current signal when it comes to faults with the power system. An algorithm for estimating fault location accurately and quickly by calculating the symmetrical components from the extracted fundamental voltage phasor and current phasor is presented. Also, to confirm the validity of digital distance relaying techniques using Kalman filtering, the experimental results obtained by using the digital simulation of power system is shown.

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Bayesian approach for the accuracy evaluating of the seismic demand estimation of SMRF

  • Ayoub Mehri Dehno;Hasan Aghabarati;Mehdi Mahdavi Adeli
    • Earthquakes and Structures
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    • 제26권2호
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    • pp.117-130
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    • 2024
  • Probabilistic model of seismic demand is the main tool used for seismic demand estimation, which is a fundamental component of the new performance-based design method. This model seeks to mathematically relate the seismic demand parameter and the ground motion intensity measure. This study is intended to use Bayesian analysis to evaluate the accuracy of the seismic demand estimation of Steel moment resisting frames (SMRFs) through a completely Bayesian method in statistical calculations. In this study, two types of intensity measures (earthquake intensity-related indices such as magnitude and distance and intensity indices related to ground motion and spectral response including peak ground acceleration (PGA) and spectral acceleration (SA)) have been used to form the models. In addition, an extensive database consisting of sixty accelerograms was used for time-series analysis, and the target structures included five SMRFs of three, six, nine, twelve and fifteen stories. The results of this study showed that for low-rise frames, first mode spectral acceleration index is sufficient to accurately estimate demand. However, for high-rise frames, two parameters should be used to increase the accuracy. In addition, adding the product of the square of earthquake magnitude multiplied by distance to the model can significantly increase the accuracy of seismic demand estimation.

위치인식 및 환경 가시화를 위한 이동 가능한 마커 위치 추정 연구 (A Study on Position Estimation of Movable Marker for Localization and Environment Visualization)

  • 양견모;곽동기;한종부;함제훈;서갑호
    • 로봇학회논문지
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    • 제15권4호
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    • pp.357-364
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    • 2020
  • Indoor localization using an artificial marker plays a key role for a robot to be used in a service environment. A number of researchers have predefined the positions of markers and attached them to the positions in order to reduce the error of the localization method. However, it is practically impossible to attach a marker to the predetermined position accurately. In order to visualize the position of an object in the environment based on the marker attached to them, it is necessary to consider a change of marker's position or the addition of a marker because of moving the existed object or adding a new object. In this paper, we studied the method to estimate the artificial marker's global position for the visualization of environment. The system calculates the relative distance from a reference marker to others repeatedly to estimate the marker's position. When the marker's position is changed or new markers are added, our system can recognize the changed situation of the markers. To verify the proposed system, we attached 12 markers at regular intervals on the ceiling and compared the estimation result of the proposed method and the actual distance. In addition, we compared the estimation result when changing the position of an existing marker or adding a new marker.

얼굴의 자세추정을 이용한 얼굴인식 속도 향상 (Improvement of Face Recognition Speed Using Pose Estimation)

  • 최선형;조성원;정선태
    • 한국지능시스템학회논문지
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    • 제20권5호
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    • pp.677-682
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    • 2010
  • 본 논문은 AdaBoost 알고리즘을 통한 얼굴 검출 기술에서 학습된 하-웨이블렛의 개별값을 비교하여 대략적인 자세를 추정하는 방법과 이를 이용한 얼굴인식 속도 향상에 대하여 기술한다. 학습된 약한 분류기는 얼굴 검출 과정 중 각각 계수값을 비교하여 각 자세의 특징에 강인한 하-웨이블렛을 선별한다. 하-웨이블렛 선별과정에는 각 항목의 유사도를 나타내는 마할라노비스 거리를 사용하였다. 선별된 하-웨이블렛을 사용하여 임의의 얼굴 이미지를 검출하였을 때 각각의 자세를 구별하는 결과를 전체 실험결과를 통해 평가한다.

Spatio-temporal estimation of air quality parameters using linear genetic programming

  • Tikhe, Shruti S.;Khare, K.C.;Londhe, S.N.
    • Advances in environmental research
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    • 제6권2호
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    • pp.83-94
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    • 2017
  • Air quality planning and management requires accurate and consistent records of the air quality parameters. Limited number of monitoring stations and inconsistent measurements of the air quality parameters is a very serious problem in many parts of India. It becomes difficult for the authorities to plan proactive measures with such a limited data. Estimation models can be developed using soft computing techniques considering the physics behind pollution dispersion as they can work very well with limited data. They are more realistic and can present the complete picture about the air quality. In the present case study spatio-temporal models using Linear Genetic Programming (LGP) have been developed for estimation of air quality parameters. The air quality data from four monitoring stations of an Indian city has been used and LGP models have been developed to estimate pollutant concentration of the fifth station. Three types of models are developed. In the first type, models are developed considering only the pollutant concentrations at the neighboring stations without considering the effect of distance between the stations as well the significance of the prevailing wind direction. Second type of models are distance based models based on the hypothesis that there will be atmospheric interactions between the two stations under consideration and the effect increases with decrease in the distance between the two. In third type the effect of the prevailing wind direction is also considered in choosing the input stations in wind and distance based models. Models are evaluated using Band Error and it was observed that majority of the errors are in +/-1 band.