• Title/Summary/Keyword: 칼만필터

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Performance Comparison of Various Extended Kalman Filter and Cost-Reference Particle Filter for Target Tracking with Unknown Noise (노이즈 불확실성하에서의 확장칼만필터의 변종들과 코스트 레퍼런스 파티클필터를 이용한 표적추적 성능비교)

  • Shin, Myoungin;Hong, Wooyoung
    • Journal of the Korea Society for Simulation
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    • v.27 no.3
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    • pp.99-107
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    • 2018
  • In this paper, we study target tracking in two dimensional space using a Extended Kalman filter(EKF), various Extended Kalman Filter and Cost-Reference Particle Filter(CRPF), which can effectively estimate the state values of nonlinear measurement equation. We introduce various Extended Kalman Filter which the Unscented Kalman Filter(UKF), the Central Difference Kalman Filter(CDKF), the Square Root Unscented Kalman Filter(SR-UKF), and the Central Difference Kalman Filter(SR-CDKF). In this study, we calculate Mean Square Error(MSE) of each filters using Monte-Carlo simulation with unknown noise statistics. Simulation results show that among the various of Extended Kalman filter, Square Root Central Difference Kalman Filter has the best results in terms of speed and performance. And, the Cost-Reference Particle Filter has an advantageous feature that it does not need to know the noise distribution differently from Extended Kalman Filter, and the simulation result shows that the excellent in term of processing speed and accuracy.

칼만필터를 이용한 해양선박의 위치제어에 대한 연구

  • Lee, Ho;Lee, Seung-Geon
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • pp.74-76
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    • 2012
  • 칼만이론 및 Unscented 변환 기반의 Unscented 칼만필터를 이용하여 동적위치제어시스템을 설계하였다. Unscented 칼만필터는 기존의 칼만필터처럼 비선형운동방정식을 선형화 할 필요없이 비선형운동방정식 그대로 사용할수 있다. Unscented 칼만필터를 이용하여 설계한 동적위치제어시스템을 MATLAB SIMULINK프로그램을 이용하여 해양선박에 대해 컴퓨터시뮬레이션을 진행하였다.

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Real-time bias correction of Beaslesan dual-pol radar rain rate using the dual Kalman filter (듀얼칼만필터를 이용한 이중편파 레이더 강우의 실시간 편의보정)

  • Na, Wooyoung;Yoo, Chulsang
    • Journal of Korea Water Resources Association
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    • v.53 no.3
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    • pp.201-214
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    • 2020
  • This study proposes a bias correction method of dual-pol radar rain rate in real time using the dual Kalman filter. Unlike the conventional Kalman filter, the dual Kalman filter predicts state variables with two systems (state estimation system and model estimation system) at the same time. Bias of rain rate is corrected by applying the bias correction ratio to the rain rate estimate. The bias correction ratio is predicted from the state-space model of the dual Kalman filter. This method is applied to a storm event with long duration occurred in July 2016. Most of the bias correction ratios are estimated between 1 and 2, which indicates that the radar rain rate is underestimated than the ground rain rate. The AR (1) model is found to be appropriate for explaining the time series of the bias correction ratio. The time series of the bias correction ratio predicted by the dual Kalman filter shows a similar tendency to that of observation data. As the variability of the bias correction increases, the dual Kalman filter has better prediction performance than the Kalman filter. This study shows that the dual Kalman filter can be applied to the bias correction of radar rain rate, especially for long and heavy storm events.

Stochastic Robust Kalman Filter using Recursive Oblique Projections (통계적 파라미터 불확실성을 고려한 사교사영 기반 선형 강인 칼만필터 설계)

  • Ra, Won-Sang;Whang, Ick-Ho
    • Proceedings of the KIEE Conference
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    • pp.288-289
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    • 2007
  • 본 논문에서는 통계적 파라미터 불확실성을 포함한 시변 선형 불확정 시스템에 대한 강인 칼만필터링 문제를 고려한다. 최소자승 관점에서 정의된 공칭 칼만필터링 문제의 목적함수를 파라미터 불확실성의 통계적 특성을 이용하여 가용한 측정행렬의 함수로 표현하고, 이로부터 근사화된 선형공간 위로의 사교사영으로 해를 도출할 수 있음을 보인다. 최종적으로 벡터 최소자승 추정기법을 동일하게 적용하여, 순환강인 칼만필터식을 유도하고, 유도된 강인 칼만필터 식이 최근 제안된 강인 최소자승 추정식에 공정잡음 및 측정잡음 분산을 반영한 보완된 형태임을 확인한다.

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

  • 김병두;이자성
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.34 no.8
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    • pp.71-78
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    • 2006
  • When a tracking filter may be designed in the Cartesian coordinate, the covariance of the measurement errors varies according to the range and the bearing of an interested target. In this paper, interacting multiple model based tracking filter is formulated in the Cartesian coordinate utilizing the analytic solution of the steady state Kalman filter, which can be able to consider the variation of the measurement error covariance. 100 Monte Carlo runs performed to verify the proposed method. The performance of the proposed method is compared with the conventional fixed gain and Kalman filter based IMM tracking filter in terms of the root mean square error. The simulation results show that the proposed approach meaningfully reduces the computation time and provides a similar tracking performance in comparison with the conventional Kalman filter based IMM tracking filter.

Radar Rainfall Adjustment by Kalman-Filter Method and Flood Simulation using two Distributed Models (칼만필터 기법에 의한 레이더 강우 보정 및 분포형 모형을 이용한 홍수 모의)

  • Bae, Young-Hye;Kim, Byung-Sik;Seoh, Byung-Ha;Kim, Hung-Soo
    • Proceedings of the Korea Water Resources Association Conference
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    • pp.147-153
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    • 2008
  • 본 연구에서는 레이더 강우를 이용하여 시공간적 변동성을 고려한 격자형 면적강우량을 산정하기 위하여 추계학적 방법인 칼만필터 기법을 이용하여 지상 강우 관측망과 레이더 강우 관측망을 조합하여 면적강우량을 산정하였다. 또한 전통적인 지상 강우량을 면적강우량으로 전환하는 기법인 Thiessen법, 역거리법, 크리깅 기법을 이용하여 면적강우량을 산정한 후 칼만필터 기법에 의해 보정된 면적 레이더 강우와 비교 하였다. 그 결과, 칼만필터 기법에 의해 보정된 레이더 강우는 실제 강우 분포와 유사한 공간분포를 가지는 원시 레이더 강우 분포를 잘 재현하면서도 강우 체적(볼륨)은 우량계 자료의 체적과 유사하게 나타났다. 그리고 칼만필터 기법에 의해 보정된 레이더 강우를 물리적 기반의 분포형 모형인 $Vflo^{TM}$ 모형과 준분포형 모형인 ModClark 모형에 적용하여 홍수유출을 모의하였다. 그 결과, $Vflo^{TM}$ 모형은 첨두시간과 첨두치가 관측 수문곡선과 유사하게 모의되었으며 ModClark 모형은 총 유출체적에서 좋은 결과를 나타냈다. 그러나 매개변수 검증에서는 $Vflo^{TM}$ 모형이 ModClark 모형보다 관측 수문곡선을 잘 재현하였다. 이를 통해 지상강우와 레이더 강우를 적절하게 조합하여 정확도 높은 면적강우량을 산정하고 분포형 수문모형과 연계하여 홍수유출모의를 실시할 경우 충분한 적용성을 가지고 있음을 확인할 수 있었다.

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Leakage Detection of Water Distribution System using Adaptive Kalman Filter (적응 칼만필터를 이용한 상수관망의 누수감시 기법)

  • Kim, Seong-Won;Choi, Doo Yong;Bae, Cheol-Ho;Kim, Juhwan
    • Journal of Korea Water Resources Association
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    • v.46 no.10
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    • pp.969-976
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    • 2013
  • Leakage in water distribution system causes social and economic losses by direct water loss into the ground, and additional energy demand for water supply. This research suggests a leak detection model of using adaptive Kalman filtering on real-time data of pipe flow. The proposed model takes into account hourly and daily variations of water demand. In addition, the model's prediction accuracy is improved by automatically calibrating the covariance of noise through innovation sequence. The adaptive Kalman filtering shows more accurate result than the existing Kalman method for virtual sine flow data. Then, the model is applied to data from two real district metered area in JE city. It is expected that the proposed model can be an effective tool for operating water supply system through detecting burst leakage and abnormal water usage.

Study on Improvement of Target Tracking Performance for RASIT(RAdar of Surveillance for Intermediate Terrain) Using Active Kalman filter (능동형 Kalman filter를 이용한 지상감시레이더의 표적탐지능력 향상에 관한 연구)

  • Myung, Sun-Yang;Chun, Soon-Yong
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.3
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    • pp.52-58
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    • 2009
  • If a moving target has a linear characteristics, the Kalman filter can estimate relatively accurate the location of a target, but this performance depends on how the dynamic status characteristics of the target is accurately modeled. In many practical problems of tracking a maneuvering target, a simple kinematic model can fairly accurately describe the target dynamics for a wide class of maneuvers. However, since the target can exhibit a wide range of dynamic characteristics, no fixed SKF(Simple Kalman filter) can be matched to estimate, to the required accuracy, the states of the target for every specific maneuver. In this paper, a new AKF(Active Kalman filter) is proposed to solve this problem The process noise covariance level of the Kalman filter is adjusted at each time step according to the study result which uses the neural network algorithm. It is demonstrated by means of a computer simulation that the tracking capability of the proposed AKF(Active Kalman filter) is better than that of the SKF(Simple Kalman Filter).

Abrupt Error Detection of Mobile Robot Using LMS Algorithm to Residuals of Kalman Filter (칼만필터의 잔류오차에 최소적응알고리즘을 적용한 이동로봇의 위치추정오차 검출기법)

  • Lee Yeon-Seok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.7
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    • pp.1332-1337
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    • 2006
  • In this paper, a noble second stage hetero-estimator is used for positioning error detection in mobile robot. Previous methods are either expensive in the case of positioning error correction or not able to detect positioning error. To overcome the latter shortage, the positioning error detection is performed using second stage hetero-estimator in motor model of mobile robot without any additional costs. A Kalman filter in the estimator gets the residual of motor current and an adaptive self-tunning filter checks the whiteness of the residual. Some simulation results show the possibility of the proposed method.

Target Models in Multi-target Tracking System (다중표적 추적시스템에서의 표적물의 모델)

  • Lee, Yeon-Seok
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.7
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    • pp.34-42
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    • 1999
  • Multi-target tracking system is defined as tracking several targets simultaneously. Kalman filter is widely used for target tracking problems. Kalman filter is known to be extremely useful as an optimal estimator but has a shortcoming of computational complexity. So a simplified estimator model which had less computational burden is proposed for a real-time implementation of multi-target tracking systems. In this paper, Kalman filter is applied to implement a real-time tracking system with a simplified target model. The proposed Kalman filter model is simpler compared with those of conventional ones, greatly reducing computation time, yet keeping the tracking abilities of the optimal Kalman filter. Through both simulations and experiments with real environments, it is demonstrated that the proposed simplified model works good in real situation with multiple to be tracked.

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