• 제목/요약/키워드: Error covariance

검색결과 271건 처리시간 0.023초

OFDM 시스템에서 비중복 프리코딩을 이용한 미상 채널 추정 방법 (Non-redundant Precoding Based Blind Channel Estimation Scheme for OFDM Systems)

  • 서방원
    • 한국통신학회논문지
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    • 제37권6A호
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    • pp.450-457
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    • 2012
  • 직교 주파수 분할 다중화 시스템에서 비중복 프리코딩을 이용한 미상 채널 추정 방식을 제안한다. 제안한 방식에서는 수신 신호에 대한 공분산 행렬을 구하고, 그 행렬의 각 원소들을 프리코딩 행렬의 각 원소로 나눔으로써 변형된 공분산 행렬을 구한다. 이 행렬의 최대 고유값에 해당하는 고유벡터를 구함으로써 채널 계수들을 추정하게 된다. 이 때, 고유 벡터를 구하기 위하여 많은 계산량을 필요로 하는 고유치 분해 기법 대신에 간단한 파워 기법을 적용함으로써 계산량을 크게 줄이게 된다. 제안하는 채널 추정 방식의 평균 제곱 오차에 대한 이론적인 값을 유도하고, 모의실험 결과와 비교함으로써 유도한 값이 실험 결과와 일치한다는 것을 확인한다. 또한, 모의실험을 통해서, 제안한 방법이 기존 방법들보다 더 우수한 채널 추정 성능과 비트 오율 성능을 나타낸다는 것을 보인다.

공군 현업 수치예보를 위한 삼차원 변분 자료동화 체계 개발 연구 (Development of the Three-Dimensional Variational Data Assimilation System for the Republic of Korea Air Force Operational Numerical Weather Prediction System)

  • 노경조;김현미;김대휘
    • 한국군사과학기술학회지
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    • 제21권3호
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    • pp.403-412
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    • 2018
  • In this study, a three-dimensional variational(3DVAR) data assimilation system was developed for the operational numerical weather prediction(NWP) system at the Republic of Korea Air Force Weather Group. The Air Force NWP system utilizes the Weather Research and Forecasting(WRF) meso-scale regional model to provide weather information for the military service. Thus, the data assimilation system was developed based on the WRF model. Experiments were conducted to identify the nested model domain to assimilate observations and the period appropriate in estimating the background error covariance(BEC) in 3DVAR. The assimilation of observations in domain 2 is beneficial to improve 24-h forecasts in domain 3. The 24-h forecast performance does not change much depending on the estimation period of the BEC in 3DVAR. The results of this study provide a basis to establish the operational data assimilation system for the Republic of Korea Air Force Weather Group.

다중표적 추적을 위한 정상상태 칼만필터 기반 IMM 추적필터 (Steady State Kalman Filter based IMM Tracking Filter for Multi-Target Tracking)

  • 김병두;이자성
    • 한국항공우주학회지
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    • 제34권8호
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    • pp.71-78
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    • 2006
  • 본 논문에서는 직교 좌표계에서 추적필터가 설계될 때, 표적의 거리와 방위에 대한 관측오차 공분산의 변화를 고려하기 위하여 정상상태 칼만필터의 해석적 해를 이용하는 IMM 추적기를 설계하였다. 제안된 정상상태 칼만필터 기반 IMM 추적기의 성능분석 및 검증을 위하여 거리의 변화가 작은 표적과 거리의 변화가 큰 표적에 대하여 각각 100회의 Monte Carlo 시뮬레이션을 수행하고, 고정이득 및 칼만필터 기반의 IMM 추적기와 RMS 오차분석을 통하여 비교하였다. 모의실험 결과로부터 제안된 방법이 칼만필터 기반 IMM 추적필터에 비하여 연산량을 크게 감소시킬 수 있으며, 유사한 추적성능을 제공할 수 있음을 확인하였다.

Detection of Voltage Sag using An Adaptive Extended Kalman Filter Based on Maximum Likelihood

  • Xi, Yanhui;Li, Zewen;Zeng, Xiangjun;Tang, Xin
    • Journal of Electrical Engineering and Technology
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    • 제12권3호
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    • pp.1016-1026
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    • 2017
  • An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

몬테-칼로 모의실험을 이용한 대기권 재진입 시스템의 불확실성 성능 평가 (Evaluation of Performance of Atmospheric Re-Entry System for the Uncertainties Using the Monte-Carlo Simulation)

  • 이대우;조겸래;오세종
    • 한국항공우주학회지
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    • 제30권7호
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    • pp.51-60
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    • 2002
  • 통계학적 해석인 몬테-칼로 모의실험은 대기권 재진입 분산의 결과인 낙하예정지역뿐만 아니라 상태변수들의 최종조건들을 조사하는데도 사용된다. 본 논문에서 재진입 분산은 위도, 경도, 고도, 뱅크각, 비행경로각, 기수 오차, 그리고 항속거리로 생성되는 $7\times7$ 공분산 행렬로 한정된다. 감속을 목표로 하는 대기권 재진입시 이것들에 영향을 미치는 오차 원인들은 대기밀도, 온도, 초기오차, 바람, 그리고 항력계수의 추정오차 등에 관련된 불확실성들로서 이들 오차의 $3{\sigma}_n$와 공칭 비행궤적을 사용해서 상태변수의 공분산 행렬은 궤적 오차 해석을 수행함으로 결정될 수 있다. 재진입에 대한 몬테-칼로법의 적용에 있어서 주요 고려할 점은 교란궤적, 뱅크역전, 그리고 이 제적들 각각에 대한 최종 낙하지점의 결정이다. 본 논문은 불확실성에 대한 결과를 공력계수와 뱅크역전의 관점에서 해석한다.

간접 되먹임 필터를 이용한 관성센서 및 초음파 속도센서 기반의 수중 복합항법 시스템 (Underwater Hybrid Navigation System Based on an Inertial Sensor and a Doppler Velocity Log Using Indirect Feedback Kalman Filter)

  • 이종무;이판묵;성우제
    • 한국해양공학회:학술대회논문집
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    • 한국해양공학회 2003년도 춘계학술대회 논문집
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    • pp.149-156
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    • 2003
  • This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o.f. equations of motion of SAUV in a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass and a depth senor. The error of the estimated position still slowly drifts in horizontal plane about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

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자율이동 로봇의 위치추정을 위한 변형된 칼만필터 방식 (Modified Kalman Filter Method for the Position Estimation of an Autonomous Mobile Robot)

  • 엄기환;강성호;김주웅
    • 한국정보통신학회논문지
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    • 제12권4호
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    • pp.781-790
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    • 2008
  • 본 논문에서는 칼만 필터 위치 추정 방식에서 노이즈 공분산에 의해 발산이 되는 문제점을 개선하기 위해 바퀴로 구성된 자율이동 로봇에 노이즈를 고려한 위치추정 방식을 제안하였다. 제안한 방식은 신경회로망을 이용한 변형된 칼만 필터 설계 방식으로, 신경회로망을 이용하여 시스템 노이즈와 측정노이즈의 공분산을 추정함으로서 발산을 방지하는 것이다. 제안한 방식의 유용성을 자체 제작한 자율이동 로봇을 대상으로 시뮬레이션 및 실험을 통하여 칼만 필터 위치 추정 방식 보다 우수함을 확인하였다.

다중경로 환경에서의 TOA방식과 TDOA방식의 측위성능 비교 (Comparisons of Error Characteristics between TOA and TDOA Positioning in Dense Multipath Environment)

  • 박지원;박지희;송승헌;성태경
    • 전기학회논문지
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    • 제58권2호
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    • pp.415-421
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    • 2009
  • TOA(time-of-arrival) and TDOA(time-difference-of-arrival) positioning techniques are commonly used in many radio-navigation systems. From the literature, it is known that the position estimate and error covariance matrix of TDOA obtained by GN(Gauss-Newton) method is exactly the same as that of TOA when the error source of the range measurement is only an IID white Gaussian noise. In case of geo-location and indoor positioning, however, multi-path or NLOS(non-line-of-sight) error is frequently appeared in range measurements. Though its occurrence is random, the multipath acts like a bias for a stationary user if it occurs. This paper presents the comparisons of error characteristics between TOA and TDOA positioning in presence of multi-path or NLOS error. It is analytically shown that the position estimate of TDOA is exactly the same as that of TOA even when bias errors are included in range measurements with different magnitudes. By computer simulation, position estimation error and error distribution are analyzed in presence of range bias errors.

Adaptive Wireless Localization Filter Containing NLOS Error Mitigation Function

  • Cho, Seong Yun
    • Journal of Positioning, Navigation, and Timing
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    • 제5권1호
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    • pp.1-9
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    • 2016
  • Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

한국형수치예보모델 자료동화에서 위성 복사자료 관측오차 진단 및 영향 평가 (Diagnostics of Observation Error of Satellite Radiance Data in Korean Integrated Model (KIM) Data Assimilation System)

  • 김혜영;강전호;권인혁
    • 대기
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    • 제32권4호
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    • pp.263-276
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    • 2022
  • The observation error of satellite radiation data that assimilated into the Korean Integrated Model (KIM) was diagnosed by applying the Hollingsworth and Lönnberg and Desrozier techniques commonly used. The magnitude and correlation of the observation error, and the degree of contribution for the satellite radiance data were calculated. The observation errors of the similar device, such as Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit-A shows different characteristics. The model resolution accounts for only 1% of the observation error, and seasonal variation is not significant factor, either. The observation error used in the KIM is amplified by 3-8 times compared to the diagnosed value or standard deviation of first-guess departures. The new inflation value was calculated based on the correlation between channels and the ratio of background error and observation error. As a result of performing the model sensitivity evaluation by applying the newly inflated observation error of ATMS, the error of temperature and water vapor analysis field were decreased. And temperature and water vapor forecast field have been significantly improved, so the accuracy of precipitation prediction has also been increased by 1.7% on average in Asia especially.