• 한국컴퓨터정보학회논문지
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• 제16권9호
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• pp.155-162
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• 2011

레이더에서 목표물을 예측하기위해서 입사 방향 추정 방법을 사용한다. 본 논문에서는 적응 배열 입사 방향 방법과 단일 지향 오차 입사 방향 추정방법을 사용하여 목표물에 대한 입사방향을 추정하였다. 적응 배열 입사 방향 방법으로 주엽 재밍과 부엽 재밍을 제거하여 목표물에 대한 신호 입사 방향을 추정하였다. 단일 지향 방법은 신호 입사 방향의 지향오차가 크기 때문에 목표물의 정확한 추정은 어렵다. 원하는 목표 신호를 수신하기 위해서는신호의 입사 방향과 지향방향사이에 지향오차가 거의 없어야 한다. 입사 방향 추정시 공분산을 구하기 위해서 생기는 지연 시간문제와 단일 지향조건을 이용하여 발생하는 지향오차 문제를 감소시켰다. 본 논문에서는 시뮬레이션을 통하여 제안된 입사 방향 추정방법이 기존의 방법에 비해 목표물 추정면에서 우수함을 보인다.

• 한국군사과학기술학회지
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• 제21권1호
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• pp.47-60
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• 2018

In this paper, we proposed a method for eliminating aiming error of unguided anti-tank rocket using improved target tracking. Since predicted fire is necessary to hit moving targets with unguided rockets, a method was proposed to estimate the position and velocity of target using fire control system. However, such a method has a problem that the hit rate may be lowered due to the aiming error of the shooter. In order to solve this problem, we used an image-based target tracking method to correct error caused by the shooter. We also proposed a robust tracking method based on TLD(Tracking Learning Detection) considering characteristics of the FCS(Fire Control System) devices. To verify the performance of our proposed algorithm, we measured the target velocity using GPS and compared it with our estimation. It is proved that our method is robust to shooter's aiming error.

• 대한방사선치료학회지
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• 제12권1호
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• pp.20-25
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• 2000

The accuracy of the target localization was evaluated by conventional and spiral CT in stereotactic radiosurgerv. Conventional and spiral CT images were obtained with geometrical phantom, which was designed to produce exact three-dimensional coordinates of several objects within 0.1mm error range. Geometrical phantom was attached by BRW headframe, intermediate head ring, and CT localizer. Twentv-seven slices of conventional CT image were scanned at 3 mm slice thickness. Spiral CT images were scanned at 3 mm slice thickness from the pitch value 1 to 3, and twenty-seven slices of image were obtained per each the pitch value. These CT images were transferred to a treatment planning system(X-knife, Radionics) by ethernet, Three-dimensional coordinates of these images measured from the treatment planning system were compared to known values of geometrical phantom. The mean localization error of the target localization of conventional CT was 1.4mm. In case of spiral CT, the error of the target localization was within 1.6mm from the pitch value 1 to 1.3, but was more than 30mm above the pitch value 1.5. In conclusion, as the localization error of spiral CT was increased in high pitch value compared to conventional CT, the application of spiral CT will be with caution in stereotactic radiosurgery.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.329-334
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• 1998

This work is concerned with the problem of tracking a maneuvering target. In this paper, an error monitoring and recovery method of perception net is utilized to improve tracking performance for a highly maneuvering tar-get. Many researches have been performed in tracking a maneuvering target. The conventional Interacting Multiple Model (IMM) filter is well known as a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation scheme. The subfilters of IMM can be considered as fusing its initial value with new measurements. This approach is also shown in this paper. Perception net based error monitoring and recovery technique, which is a kind of geometric data fusion, makes it possible to monitor errors and to calibrate possible biases involved in sensed data and extracted features. Both detecting a maneuvering target and compensating the estimated state can be achieved by employing the properly implemented error monitoring and recovery technique. The IMM filter which employing the error monitoring and recovery technique shows good tracking performance for a highly maneuvering target as well as it reduces maximum values of estimation errors when maneuvering starts and finishes. The effectiveness of the pro-posed method is validated through simulation by comparing it with the conventional IMM algorithm.

• 산업기술연구
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• 제9권
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• pp.67-77
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• 1989

This study is concerned with the accuracy, the pattern of error with which subjects can interpolate the location of a pointer or a target between two graduation markers with various size on CRT display. Stimuli were graphic images on CRT with a linear, end-marked, ungraduated scales having a target for t base-line sizes. The location of a target is estimated in units over the range 1-99. Smallest error of estimates was at the near ends and middle of the base-line. The median error was less 2 units, modal error was 1, and most error(;99.6%) was within 10. Subjects had a more tendency to overestimate than to underestimate at the left-part of base-line in all siges, and an opposite tendency at the right-part. A proper size to minimize the interpolation error exists such that size 500. It is suggested that interpolation of fifths and even tenths will give a reguired accuracy for certain situations, and relative location and base-line size has a relevant attribute to interpolate.

• 전자공학회논문지
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• 제53권2호
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• pp.133-140
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• 2016

해안 수중 감시를 위하여 분산센서망를 해안에 설치하고, 이를 이용하여 표적을 탐지하고 표적의 위치를 추정하는 연구가 많이 이루어지고 있다. Zhou 등은 표적 탐지만 가능한 간단한 구조의 센서들로 구성된 분산센서망에서 표적을 탐지한 센서들의 위치 정보를 활용하여 표적의 위치를 추정하는 기법을 제안하였다. Zhou 등이 제안한 기법은 다른 기존의 기법에 비해 표적탐지 신호의 전파모델에 대한 파라미터들을 별도로 추정할 필요가 없고, 연산량이 적으며, 분산센서망에서 적은 량의 데이터만 송수신하여도 된다. 그러나 Zhou 기법은 표적의 위치 추정오차가 크다. Ryu는 추정오차를 줄이기 위하여 Zhou 기법을 수정하였다. 수정된 Zhou 기법은 Zhou 기법보다 추정성능이 향상되었지만, 여전히 비교적 큰 추정오차를 가지고 있다. 본 논문에서는 수정된 Zhou 기법으로 구한 표적의 방위각을 나타내는 직선과 표적을 탐지한 센서들과의 기하학적 구조를 고려한 표적위치 추정기법을 제안하였으며, 수정된 Zhou 기법에 기반을 두고 있다. 제안한 기법의 표적위치 추정성능이 Zhou 기법과 수정된 Zhou 기법 보다 향상되었음을 컴퓨터 시뮬레이션을 통하여 확인하였다.

• 한국군사과학기술학회지
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• 제18권1호
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• pp.84-92
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• 2015

This paper proposes a new approach to reduce the target estimation error of the measurement angle, especially applied to the medium and long range surveillance radar. If the target has no maneuver and no change in heading direction for a certain time interval, the predicted angle of interacting multiple model(IMM) from the previous track information can be used to reduce the angle estimation error. The proposed method is simulated in 2 scenarios, a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new fusion solution(weighted IMM) with the predicted azimuth and the measured azimuth is worked properly in the two scenarios.

• 한국군사과학기술학회지
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• 제14권3호
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• pp.517-523
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• 2011

The estimation filter in radar systems must track targets' position within low tracking error. In the Multi-Function Radar(MFR), ${\alpha}-{\beta}$ filter and Kalman filter are widely used to track single or multiple targets. However, due to target maneuvering, these filters may not reduce tracking error, therefore, may lost target tracks. In this paper, a target tracking filter based on particle filtering algorithm is proposed for the MFR. The advantage of this method is that it can track targets within low tracking error while targets maneuver and reduce impoverishment of particles by the proposed resampling method. From the simulation results, the improved tracking performance is obtained by the proposed filtering algorithm.

• International Journal of Contents
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• 제7권3호
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• pp.1-5
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• 2011

It has been an interesting challenge to find a good classifier for imbalanced data, since it is pervasive but a difficult problem to solve. However, classifiers developed with the assumption of well-balanced class distributions show poor classification performance for the imbalanced data. Among many approaches to the imbalanced data problems, the algorithmic level approach is attractive because it can be applied to the other approaches such as data level or ensemble approaches. Especially, the error back-propagation algorithm using the target node method, which can change the amount of weight-updating with regards to the target node of each class, attains good performances in the imbalanced data problems. In this paper, we analyze the relationship between two optimal outputs of neural network classifier trained with the target node method. Also, the optimal relationship is compared with those of the other error function methods such as mean-squared error and the n-th order extension of cross-entropy error. The analyses are verified through simulations on a thyroid data set.

• 대한원격탐사학회지
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• 제33권5_1호
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• pp.547-557
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• 2017

본 연구에서는 탐지하고자 하는 표적신호를 초기 엔드멤버로 하여 Iterative Error Analysis를 통해 배경물질들의 반사 스펙트럼을 순차적으로 엔드멤버로 추출하고, 추출된 엔드멤버들을 이용하여 분광 혼합분석함으로써 표적물질의 분포를 탐지하는 새로운 초분광 표적탐지 기법을 제안한다. 제안된 기법에서는 표적물질에 대한 점유율의 변화가 주어진 문턱값보다 작아질 때 엔드멤버 추출을 위한 반복을 멈추게 된다. 이 기법은 Orthogonal Subspace Projection과 같은 모델 기반 표적 탐지기법들과 달리 사전에 엔드멤버들을 확보해야 할 필요가 없으며, Matched Filter와 같은 확률론적 표적 탐지 기법들과 달리 배경 전체를 하나의 신호로 특징화하지 않기 때문에 표적의 희소성 여부에 의한 영향을 받지 않는다는 장점을 가지고 있다. 실제 항공 초분광 영상자료 및 다양한 인공 표적물질들이 삽입된 모의 초분광 영상자료를 이용한 실험 결과, 제안된 방법이 희소 및 비 희소 표적의 탐지에 매우 효과적임이 확인되었다. 제안된 방법은 표적 물체 탐지뿐만 아니라 광물, 오염물질 등 자원 및 환경 분야에서 다양한 피복 물질을 탐지하는데 효과적으로 사용될 수 있을 것으로 기대된다.