• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.22-29
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• 2016

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target detection technique has been considered as a difficult technique. In this paper, we describe the basic concept of Fractional Fourier transform and optimal transform order. Then we analyze the relationship between time-frequency characteristics of an LFM signal and its spectrum using Fractional Fourier transform. Based on the analysis results, we present active sonar target detection method. To verify the performance of proposed methods, we compared the results with conventional FFT-based matched filter. The experimental results demonstrate the superiority of the proposed method compared to the conventional method in the aspect of AUC(Area Under the ROC Curve).

• 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.

• 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).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.355-364
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• 2012

Target processing mechanisms are necessary to collect target information, real-time data fusion, and tactical environment recognition for cooperative engagement ability. Among these mechanisms, the target tracking starts from predicting state of speed, acceleration, and location by using sensors' measurements. However, it can be a problem to give the reliability because the measurements have a certain uncertainty. Thus, a technique which uses multiple sensors is needed to detect the target and increase the reliability. Also, data fusion technique is necessary to process the data which is provided from heterogeneous sensors for target tracking. In this paper, a target tracking algorithm is proposed based on probabilistic data association(PDA) by fusing radar and ESM sensor measurements. The radar sensor's azimuth and range measurements and the ESM sensor's bearing-only measurement are associated by the measurement fusion method. After gating associated measurements, state estimation of the target is performed by PDA filter. The simulation results show that the proposed algorithm provides improved estimation under linear and circular target motions.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1305-1318
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• 2012

Image segmentation is one of the difficult research problems in machine vision and pattern recognition field. A commonly used segmentation method is the Otsu method. It is simpler and easier to implement but it fails if the histogram is unimodal or similar to unimodal. And if some target area is smaller than background object, then its histogram has the distribution close to unimodal. In this paper, we proposed an improved image segmentation method based on 1D Otsu method for a small target detection. To overcome drawbacks by unimodal histogram effect, we depressed the background histogram using a logarithm function. And to improve a signal to noise ratio, we used a local average value by the neighbor window for thresholding using 1D Otsu method. The experimental results show that our proposed algorithm performs better segmentation result than a traditional 1D Otsu method, and needs much less computational time than that of the 2D Otsu method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.6
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• pp.579-589
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• 2004

The radar signals are generally very sensitive to relative orientations between radar and target. Thus, the performance of a target recognition system significantly deteriorates as the region of aspect angles becomes broader. To address this difficulty, in this paper, we propose a method based on the multi-aspect information in order to improve the classification capability ever for a wide angular region. First, range profiles are used to extract feature vectors based on the central moments and principal component analysis(PCA). Then, a classifier with the use of multi-aspect information is applied to them, yielding an additional improvement of target recognition capability. There are two different strategies among the classifiers that can fuse the information from multi-aspect radar signals: independent methodology and dependent methodology. In this study, the performances of the two strategies are compared within the frame work of target recognition. The radar cross section(RCS) data of six aircraft models measured at compact range of Pohang University of Science and Technology are used to demonstrate and compare the performances of the two strategies.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.91-97
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• 2019

When a radar tracks the warhead of a ballistic missile, decoys of a ballistic missile put a heavy burden on the radar resource management tracking the targets. To reduce this burden, it is necessary to be able to separate the signal of the warhead from the received dynamic radar cross section (RCS) signal on the radar. In this paper, we propose the method of separating the dynamic RCS of each target from the received signal by the Hough transform which extracts straight lines from the image. The micro motion of the targets was implemented using a 3D CAD model of the warhead and decoys. Then, we calculated the dynamic RCS from the 3D CAD model having micromotion and verified the performance by applying the proposed algorithm. Simulation results show that the proposed method can separate the signals of the warhead and decoys at the signal-to-noise ratio (SNR) of 10dB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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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.

• 전기의세계
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• v.42 no.6
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• pp.38-45
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• 1993

앞으로 21세기 기술선도사업으로 고속성 및 병렬성의 장점을 지닌 퓨리에 광 신호처리 기술은 광통신 기술, 광소자 기술등과 병행하여 미래의 종합 정보통신 시스템에서 커다란 비중을 차지할 것으로 예상되며 특히, 자동감시, 로보트 비젼등 산업적 응용분야뿐만 아니라, 미사일 유도, 자동표적 인식 및 추적등의 분야에서 첨단기술로서 그 응용이 크게 기대되어 이에 대한 연구 개발이 활발히 진행되고 있다.

• Proceedings of the SCSK Conference
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• 1994.07a
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• pp.54-66
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• 1994

외부 환경에 대한 장벽으로서 피부기능의 고전적인 개념은 중요한 신진대사와 면역학적 작용이 일어나는 것을 인식함으로써 확장 되었다. 피부의 면역학적 역할은 면역적 상해의 단순한 표적 이라는 것에서 피부와 연관된 피부와 면역반응의 개시와 조절에서 활발한 역할을 수행하는 것으로 확대되었다. 본 총설은 면역계의 토대가 되는 중요한 기작을 알아보고자 한다. 또한 Langerhans cells와 keratinocytes 뿐만아니라 항산화제, 자와선, 지방산 등이 피부 노화에 미치는 영향에 대해 알아보고자 한다.