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Sliding Window Filtering for Ground Moving Targets with Cross-Correlated Sensor Noises
송일영,Jin Mo Song,Woong Ji Jeong,Myoung Sool Gong 한국센서학회 2019 센서학회지 Vol.28 No.3
This paper reports a sliding window filtering approach for ground moving targets with cross-correlated sensor noise and uncertainty. In addition, the effect of uncertain parameters during a tracking error on the model performance is considered. A distributed fusion sliding window filter is also proposed. The distributed fusion filtering algorithm represents the optimal linear combination of local filters under the minimum mean-square error criterion. The derivation of the error cross-covariances between the local sliding window filters is the key to the proposed method. Simulation results of the motion of the ground moving target a demonstrate high accuracy and computational efficiency of the distributed fusion sliding window filter.
Distributed Fusion Estimation for Sensor Network
송일영,Jin Mo Song,Woong Ji Jeong,Myoung Sool Gong 한국센서학회 2019 센서학회지 Vol.28 No.5
In this paper, we propose a distributed fusion estimation for sensor networks using a receding horizon strategy. Communication channels were modelled as Markov jump systems, and a posterior probability distribution for communication channel characteristics was calculated and incorporated into the filter to allow distributed fusion estimation to handle path loss observation situations automatically. To implement distributed fusion estimation, a Kalman-Consensus filter was then used to obtain the average consensus, based on the estimates of sensors randomly distributed across sensor networks. The advantages of the proposed algorithms were then verified using a large-scale sensor network example.
Distributed Fusion Moving Average Prediction for Linear Stochastic Systems
송일영,Jin Mo Song,Woong Ji Jeong,Myoung Sool Gong 한국센서학회 2019 센서학회지 Vol.28 No.2
This paper is concerned with distributed fusion moving average prediction for continuous-time linear stochastic systems with multiple sensors. A distributed fusion with the weighted sum structure is applied to the optimal local moving average predictors. The distributed fusion prediction algorithm represents the optimal linear fusion by weighting matrices under the minimum mean square criterion. The derivation of equations for error cross-covariances between the local predictors is the key of this paper. Example demonstrates effectiveness of the distributed fusion moving average predictor.
이산 불확실성 시간 지연 시스템을 위한 이동 구간 칼만 필터링
송일영(Il-Young Song),전문구(Moongu Jeon) 한국정보기술학회 2011 Proceedings of KIIT Conference Vol.2011 No.5
본 논문에서는 다중 센서를 가지고 있는 이산 불확실성 시간 지연 시스템을 위한 이동 구간 칼만 필터링을 제안한다. 제안된 필터링 알고리즘은 실제 시스템 모델 또는 측정치의 불확실성에 대하여 더욱 견실하고 정확한 시스템의 상태 추정을 위해 이동 구간 기법을 적용한다. 상태 추정에 쓰인 이동 구간 칼만 필터는 가장 최근의 시간 간격 상에서 유한한 측정치를 활용한다. 본 논문의 핵심은 시스템 모델에 시간 지연을 고려한 이동구간 칼만 필터의 평균 및 분산식 유도이다. 시뮬레이션 결과는 동적 모델의 불확실성에 대해 이동 구간 필터가 견실하고 정확한 시스템 상태 추정을 할 수 있음을 입증한다. Here, we define a receding horizon estimator (filter) for discrete-time stochastic linear systems with delays in state and measurement. Novel filtering algorithm is designed based on the receding horizon strategy in order to achieve high estimation accuracy and stability under parametric uncertainties. New receding horizon filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for receding horizon mean and covariance of system state with an arbitrary number of time delays. Numerical example demonstrates the proposed algorithm is more robust and more accurate than Kalman filter against dynamic model uncertainties.
송일영(Il-Young Song),윤주홍(Ju-Hong Yoon),김두용(Du-Yong Kim),김용훈(Yong-Hoon Kim),신 블라디미르(Vladimir Shin) 한국정보기술학회 2009 Proceedings of KIIT Conference Vol.2009 No.-
본 연구는 94 ㎓ 대역의 polarimetric 라디오미터를 이용하여 도로 노면에 대한 특성을 측정, 분석하기위하여 아스팔트 시료를 대상으로 실험하였다. 도로 노면을 젖은 상태 또는 결빙상태로 가정하여 두 편파 모드에 대한 밝기 온도를 측정하였다. 실험 결과 도로 노면의 상태에 따라 밝기온도의 차이가 큰 것으로 나타났다. 이는 실제 도로면의 상태를 측정하는 정보로서 도로면의 밝기온도 정보를 측정하는 것이 효율적임을 입증한다. An experimental study aiming at detecting different road conditions (Wet and Ice) by means of 94 ㎓ dual-channel polarimetric radiometer has been conducted in open-air laboratory using a sample of asphalt as target. The brightness temperature is measured at horizontal and vertical polarization for different road surface conditions. The measurements carried out on the target have pointed out that a 94 ㎓ band polarimetric radiometer is able to judge the different states of the road surface.