• Journal of the Korean Institute of Intelligent Systems
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• 제15권5호
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• pp.593-598
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• 2005

The standard Kalman filter has been used to estimate the states of the target, but in the presence of a maneuver, its error is occurred and performance may be seriously degraded. To solve this problem, this paper presents a new intelligent tracking algorithm using the fuzzy Kalman filter. In this algorithm, the unknown acceleration is regarded as an additive process noise by using the fuzzy logic based on genetic algorithm(GA) method. And then, the modified filter is corrected by the new update equation method which is a fuzzy system using the relation between the filter residual and its variation. To shows the feasibility of the suggested method with only one filter, the computer simulations system are provided, this method is compared with multiple model method.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제21권1호
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• pp.229-236
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• 2017

In general, an error budget of monopulse radar is proposed by manufacturer who assuming that all of external enviromental error resources such as multipath, glint, dynamic lag variation are removed. So until now, a measurement uncertainty of monopulse radar can be discussed including external enviromental error resources. In this paper, it is described that which kinds of error resource can effect on monopulse radar measurement uncertainty for different target property. To prove it experimentally, at first a simulation result is described assuming that all of external enviromental error resources are removed. It only includes receiver thermal noise. And then, monopulse radar measurement uncertainty estimation results tracking on calibration target which is fixed on specific position, calibration sphere which is moving slowly, weapon systems firing test which is moving fast are described quantitativly. All of these targets have different dynamic property.

• Journal of the Institute of Electronics Engineers of Korea SC
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• 제49권3호
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• 제19권11호
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• pp.43-52
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• 2014

In this paper, we propose the target detection method using image displacement, and classification method using SURF(Speeded Up Robust Features) feature points and BAS(Beam Angle Statistics) in infrared images. The SURF method that is a typical correspondence matching method in the area of image processing has been widely used, because it is significantly faster than the SIFT(Scale Invariant Feature Transform) method, and produces a similar performance. In addition, in most SURF based object recognition method, it consists of feature point extraction and matching process. In proposed method, it detects the target area using the displacement, and target classification is performed by using the geometry of SURF feature points. The proposed method was applied to the unmanned target detection/recognition system. The experimental results in virtual images and real images, we have approximately 73~85% of the classification performance.

• Journal of the Korea Society for Simulation
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• 제20권4호
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• pp.1-11
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• 2011

In the development phase of a torpedo, the effectiveness analysis is carried out to predict the performance and to learn how to use the torpedo. In order to obtain reliable data, it is required to model the tactical situation closely to the actual one. Because the submarine is a target of a lightweight torpedo, the anti-torpedo countermeasures of a submarine such as evasive maneuvering and TACM (Torpedo Acoustic Counter Measure) should be modeled in detail. In this paper, the evasive maneuvering is modeled reflecting the movement characteristics of the submarine. Furthermore various TACMs such as a floating-type decoy, a self-propelled decoy and jammers are also modeled. Then, effectiveness of a lightweight torpedo is measured and analyzed using the simulation program which is developed through the above modeling procedure.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• 제27권6호
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• pp.557-565
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• 2016

It is very difficult to intercept the missiles because of the small radar cross-section and the high maneuverability. In addition, due to the decoy with the similar motion parameters, additional features other than those of the translation motion parameters need to be developed. In this paper, for the successful recognition of missiles, we propose an efficient method to extract micro-motion parameters and scatterers of the missile engaged in the micro motion. The proposed method extracts motion parameters and scatterers by using the matching score between the modeled micro-Doppler function and the time-frequency binary image as a cost function. Simulation results using a target composed of the point scatterer show the parameters and the scatterers were accurately extracted.

• Journal of the Korean Institute of Intelligent Systems
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• 제23권4호
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• pp.304-309
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• 2013

This paper proposes a intelligent approach on range decision of figure of merit. Unknown range of the underwater target and the non-fixed signal excess make the uncertainty for the tracking process. Using the input data of signal excess related to the range, we establish the rule of the fuzzy set and the original data acquired by sonar can be transformed to the fuzzified data set. To reduce the error arisen from the unexpected data, we use the new data transformed in fuzzy set. The piecewise relations of the min value, max one, and the mean one are calculated. The three values are used for the expected range of the underwater target. By analysing the fluctuation of the data, we can expect the target's position and the characteristics of the maneuvering. The examples are presented to show the performance and the effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제25권12호
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• pp.1826-1834
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• 2021

In this paper, we check the possibility of continuous tracking when photographing unknown space objects in a short period of time in an optical observation system on the ground. Simulated observation data were generated for target limited to low-orbit areas. The performance index of the prediction error was set in consideration of the property of targets. Kalman Filter was applied to predict the next location of the target. A constant velocity/acceleration dynamic model was applied to the two axes of the azimuth/elevation of the unknown space object respectively. As a result of performing the Monte Carlo simulation, the maximum error ratio of the maximum nonlinear section was less than 2%, which could be determined to ensure continuous tracking. The CA model had little change in the prediction error value for each case, making it more suitable for tracking unknown space objects. This analysis could provide a foundation for determining the orbit of unknown space objects using optical observation.

• Proceedings of the Acoustical Society of Korea Conference
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• 한국음향학회 1999년도 학술발표대회 논문집 제18권 2호
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• pp.161-164
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• 1999

본 논문에서는 표적 추적 시스템에서 센서 어레이에 입사되는 표적신호에 대한 센서 출력 신호간의 지연시간 추정(TDE:Time Delay Estimation)을 위해 백색상호 상관법(CSP:Cross-Power Spectrum Phase Analysis)을 이용한다. 그러나 음파의 다중경로 전달특성 및 배경잡음의 영향으로 인해 CSP계수는 많은 클러터(Clutter)를 포함하게 되고 결국 방위 추정 오차의 요인이 된다. 따라서 센서 어레이 중심좌표를 기준으로 대칭 배열된 센서쌍(Pair)에 대한 CSP계수를 동기가산 하여 실제 표적 방향 이외의 방향정보를 제거하는 방법을 제안한다. 시간에 따라 각도를 변침하는 표적에 대한 표적기동분석 (BOTMA:Bearings Only Target Motion Analysis)을 위해 매 관측시간마다 동기가산을 행한 CSP결과를 누적하여 방위각 궤적을 형성하였을 때 시간 Window에 따라 약간의 차이는 있지만 약 10dB의 궤적 추적 성능을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• 제44권3호
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• pp.51-57
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• 2007

Without human dynamics effects, the manually operated target tracking system has poor performance or instability in real environments. The tracking system is invalid when a human is added to the control loop as a real time delay, because input signals are generated by human operator to reduce the errors between target and gun. In this paper, we consider the human operator as a part of controller and modeling the human operator as a first-order model to generate the intentional force. But it is known that human modeling is not easy because of disturbance or noise of the vehicle while moving for the target. We performed a variety of experiments with real plant to identify the model's parameters and verify the proposed operator model's efficiency.