• 제목/요약/키워드: estimation in measurement

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변별기 추정방식을 적용한 다기능 레이다용 거리 및 속도 측정 알고리즘 성능 분석 (Performance Analysis of Range and Velocity Measurement Algorithm for Multi-Function Radar using Discriminator Estimation Method)

  • 최병관;이범석;김환우
    • 대한전자공학회논문지SP
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    • 제42권1호
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    • pp.109-117
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    • 2005
  • 거리 및 속도 측정 알고리즘은 거리 및 도플러 주파수 영역에서 등 간격으로 구성된 정합필터 출력을 이용하여 정밀한 표적 위치를 추정하는 과정이다. 특히 다기능 레이다용 측정 알고리즘은 동시에 다 표적 추적이 가능하도록 정밀도 뿐만 아니라 수행시간에 대한 고려가 필요하다. 본 논문에서는 모노 펄스(monopulse) 레이다 각도추정에 사용되는 변별기(discriminator)추정방식을 거리 및 속도 측정에 적용하여 알고리즘 성능분석 결과를 제시한다. 적용된 추정방법은 추정 시 수행시간이 일정하므로 다중 표적 추적에 적합하다. 하지만 최소한의 채널 출력만을 이용한 추정방법이므로 측정 정밀도에 대한 고려가 필요하다. 컴퓨터 모의실험을 통해 기존 무게중심 추정방식의 측정 알고리즘과 정밀도 측면에서 성능을 비교하여 적용한 방법의 우수성을 보이고, 또한 펄스 폭, 채널 간격 등 프로세싱 변수 변화에 따른 RMS 에러 계산을 통해 알고리즘 자체 특성을 분석한다.

선박 방사소음의 측정방법 및 정확도 해석 (Ship Radiated Noise Measurement Methods and Accuracy Analysis)

  • 이필호;윤종락
    • 한국소음진동공학회논문집
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    • 제15권6호
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    • pp.738-748
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    • 2005
  • The ship radiated noise level fluctuates by the difference of interference and reverberation according to measurement methods and environmental conditions. These phenomena cause error of the source level estimation even in the same environment conditions. This paper describes a quantitative analysis and a reduction method for an error value to the source level estimation in spatial and temporal interference environment. The design criteria of the radiated noise measurement array composed of omni-directional hydrophones and the source level accuracy in the deep water range are given. The source level accuracy in the shallow water range is also derived based on the statistical model of the multiple reflection paths. The results are verified using the water tank experiment and the sea trial.

측정 ANOVA의 분산성분에 의한 게이지 R&R 추정 (Estimation of Gauge R&R by Variance Components of Measurement ANOVA)

  • 최성운
    • 대한안전경영과학회지
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    • 제12권1호
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    • pp.199-205
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    • 2010
  • The research proposes the three-factor random measurement models for estimating the precision about operator, part, tool, and various measurement environments. The combined model with crossed and nested factors is developed to analyze the approximate F test by degrees of freedom given by Satterthwaite and point estimation of precisions from expected mean square. The model developed in this paper can be extended to the three useful models according to the type of nested designs. The study also provides the three-step procedures to evaluate the measurement precisions using three indexes such as SNR(Signal-To-Noise Ratio), R&R TR(Reproducibility&Repeatability-To-Total Precision Ratio), and PTR(Precision-To-Tolerance Ratio), The procedures include the identification of resolution, the improvement of R&R reduction, and the evaluation of precision effect.

전류측정성분과 불량정보 검출을 고려한 전력계통에서의 상태추정에 관한 연구 (State Estimation Considering Current Measurement Component and Bad Data Detection)

  • 김준현;이종범
    • 대한전기학회논문지
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    • 제35권7호
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    • pp.261-271
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    • 1986
  • This paper describes a method for the state estimation considering current measurement component and detection of the bad data. The state values are estimated by weighted least square method in which measurement vector included bus injection current and line current. The bad data are detected using standardized variable of normal distribution and identified using sensitivity coefficients. When the bad data were occured by the bad measurement values. The results of the application to the model power system reveal the effectiveness of the presented algorithms.

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Semiparametric Bayesian Estimation under Structural Measurement Error Model

  • Hwang, Jin-Seub;Kim, Dal-Ho
    • Communications for Statistical Applications and Methods
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    • 제17권4호
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    • pp.551-560
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    • 2010
  • This paper considers a Bayesian approach to modeling a flexible regression function under structural measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under structural measurement error model without a semiparametric component.

Semiparametric Bayesian estimation under functional measurement error model

  • Hwang, Jin-Seub;Kim, Dal-Ho
    • Journal of the Korean Data and Information Science Society
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    • 제21권2호
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    • pp.379-385
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    • 2010
  • This paper considers Bayesian approach to modeling a flexible regression function under functional measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under functional measurement error model without semiparametric component.

추정모델에 의한 화력발전 플랜트 계측데이터의 검증 및 유효화 (Estimation Model-based Verification and Validation of Fossil Power Plant Performance Measurement Data)

  • 김성근;윤문철;최영석
    • 한국정밀공학회지
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    • 제17권2호
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    • pp.114-120
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    • 2000
  • Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification & validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.

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수동형 탐색기의 시선 각속도 측정을 이용한 접근속도 추정 (Missile closing velocity estimation based on the LOS rate measurement)

  • 탁민제;류동영
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.268-273
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    • 1991
  • Missile and target closing velocity is used in the proportional navigation(PN) missile guidance loop. But it is difficult to estimate the closing velocity when passive seeker is used and only the Line-of-Sight(LOS) rate is available in the guidance loop. In this study, new closing velocity estimation method is developed. This method uses LOS rate measurement only and uses some characteristics of PN guidance law. The Lyapunov method is used to analyze the stability of the developed estimation method.

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Improved extended kalman filter design for radar tracking

  • Park, Seong-Taek;Lee, Jang-Gyu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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    • pp.153-156
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    • 1996
  • A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.

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표준 측정치의 오차를 고려한 다변량 계기 교정 절차 (A Multivariate Calibration Procedure When the Standard Measurement is Also Subject to Error)

  • 이승훈
    • 대한산업공학회지
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    • 제19권2호
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    • pp.35-41
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    • 1993
  • Statistical calibration is a useful technique for achieving compatibility between two different measurement methods, and it usually consists of two steps : (1) estimation of the relationship between the standard and nonstandard measurements, and (2) prediction of future standard measurements using the estimated relationship and observed nonstandard measurements. A predictive multivariate errors-in-variables model is presented for the multivariate calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the maximum likelihood (ML) estimation method is considered. It is shown that the direct and the inverse predictors for the future unknown standard measurement are the same under ML estimation. Based upon large-sample approximations, the mean square error of the predictor is derived.

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