• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.365-367
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• 2013

해상감시레이더는 관제지역의 해상교통정보를 수집하는 해상교통관제시스템의 주요 센서로, 다양한 운동 특성을 갖는 선박의 안정적인 추적과 위치, 속도, 침로 등의 정확한 정보를 제공하는 것은 VTS 성능 개선 및 서비스 고도화에 매우 중요한 요소 기술이다. 본 논문에서는 해상교통관제시스템에서 다양한 기동 특성을 갖는 선박의 정확한 추적을 위하여 상호작용 다중필터(IMM) 추정기를 이용한 추적 알고리즘을 설계하고, 모의실험을 통하여 필터 뱅크의 구성에 따른 성능 비교 및 분석을 수행한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.497-502
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• 2002

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, a DNA coding-based interacting multiple model (DNA coding-based W) method is proposed. The proposed method can overcome the mathematical limits of conventional methods by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive IMM algorithm and the GA-based IMM method in computer simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.106-111
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• 2011

Video-based detection and tracking of moving objects has been widely used in real-time monitoring systems and a videoconferencing. Also, because object motion tracking can be expanded to Human-computer interface and Human-robot interface, Moving object tracking technology is one of the important key technologies. If we can track a specified object in an environment of multiple moving objects, then there will be a variety of applications. In this paper, we introduce a specified object motion tracking using particle filter. The results of experiments show that particle filter can achieve good performance in single object motion tracking and a specified object motion tracking in an environment of multiple moving objects.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.496-498
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• 2000

기존의 웹 기반 3차원 가상환경 분야에 대한 연구는 시각적인 면에서 이전의 웹 컨텐츠에 비해 많은 향상이 있었다. 그러나 내부 객체들간의 다양한 상호작용이나 참여자를 대신하는 아바타(Avatar)의 행위(Behavior)표현에 대해서는 많은 한계를 가지고 있다. 본 논문에서는 아바타를 포함한 가상 객체간의 상호작용과 행위의 유형을 정의하며 이를 지원할 수 있는 가상환경서버를 설계하고 구현한다. 또한, 다중사용자의 참여로 인해 발생할 수 있는 서버의 성능저하를 줄이기 위한 방법론으로서 지역관리 및 메시지 필터링 기법을 제안한다. 구현된 시스템은 가상 쇼핑몰 등의 응용분야에 실제 적용이 가능하다.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.387-393
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• 2002

The enhancement technique of noise signal using mixture HFM (Midden Filter Model) are proposed. Given the parameters of the clean signal and noise, noisy signal is modeled by a linear state-space model with Markov switching parameters. Estimation of state vector is required for estimating original signal. The estimation procedure is based on mixture interacting multiple model (MIMM) and the estimator of speech is given by the weighted sum of parallel Kalman filters operating interactively. Simulation results showed that the proposed method offers performance gains relative to the previous results with slightly increased complexity.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.1-2
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• 2016

다중 스레드 기반 병렬 프로그램에서의 자료경합 탐지는 동시에 수행되는 스레드 간의 비결정적인 상호작용 때문에 탐지하기 어려운 것으로 잘 알려져 있다. 동적 분석기술을 사용하여 자료경합을 탐지할 경우 프로그램 수행의 감시와 충돌하는 모든 메모리 연산의 분석을 위해 추가적인 오버헤드가 발생한다는 단점이 있다. 이러한 동적 분석의 추가적인 오버헤드를 줄이는 방법으로 감시 필터링 기술이 소개되고 있으며, 본 논문에서는 동적 자료경합 탐지를 위한 감시 필터링 기술 중 OpenMP 디렉티브 병렬 프로그램에 적용 가능한 두 기술을 대상으로 실용성과 효율성을 실험적으로 비교한다.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.18-27
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• 2020

In order to estimate the launch point of a high-speed vehicle, predicting the various characteristics of the vehicle's movement, such as drag and thrust, must be preceded by the estimation. To predict the various parameters regarding the vehicle's characteristics, we build the IMM filter specialized in predicting the parameters of the post-launch phase based on flight dynamics. Then we estimate the launch point of the high-speed vehicle using Inverse Dynamics. In addition, we assume the arbitrary error level of the radar for accuracy of the prediction. We organize multiple-dimensioned IMM structures, and figure out the optimal value of parameters by comparing the various IMM structures. After deriving the optimal value of parameters, we verify the launch point estimation error under certain error level.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.131-136
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• 2003

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the states of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.136-142
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• 2007

This paper proposes a new approach on nonlinear maneuvering target tracking. In this paper, proposed algorithm is the Kalman filter based on the adaptive interactive multiple model using the concept of predicted impact point and utilize modified Kalman filter regarding the error between measurement position and predicted impact point. The unknown target acceleration is regarded as an additional process noise to the target model, and each sub-model is characterized in accordance with the valiance of the overall process noise which is obtained on the basis of each acceleration interval. To compensate the decreasing performance of Kalman filter in nonlinear maneuver, we construct optional algorithm to utilize proposed method or Kalman filter selectively. To effectively estimate the acceleration during the target maneuvering, the rapid increase of the noise scale is recognized as the acceleration to be used in maneuvering target's movement equation. And a few examples are presented to show suggested algorithm's executional potential.