• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1924-1925
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• 2011

본 논문에서는 비선형 기동을 하는 기동표적의 추정된 잡음을 분석하여 표적의 기동패턴을 분석하는 알고리즘을 제시하고자 한다. 기동표적의 추정위치와 측정치에서 발생하는 잡음을 가속도와 순수 잡음으로 분리하고 분리된 성분을 분석하여 표적의 기동 패턴을 인식하고 동시에 추적을 실시하는 알고리즘을 구성한다. 잡음의 분리는 퍼지 클러스터링(FCM : Fuzzy C-means Clustering) 기법을 이용하여 적절한 추정값을 이용한다. 추정된 표적의 속도와 가속도, 잡음을 재 구성하여 기동표적의 기동패턴을 분석하고, 동시에 추적을 실시한다. 위의 과정을 통해 가속도를 분리한 후 비선형성을 지닌 기동표적의 기동패턴을 선형화 하여 칼만필터를 이용 잡음을 분리하고 가속도를 다시 보상하여 추적 알로리즘을 구성한다. 그리고 제안된 알고리즘의 수행 가능성을 보여 주기 위하여 몇 가지 예를 제시하였다.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.93-100
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• 2000

Target signal feature parameters are very important to classify target by active sonar. Two highly correlated broad band pulses separated by time T have a time separation pitch(TSP) of 1/T Hz which is equal to the trough-to-trough or peak-to-peak spacing of its spectrum. In this study, TSP informations which represent feature of each target signal were effectively extracted by the FFT. The extracted TSP feature parameters were also applied to the pattern recognition algorithm to classify target and to analyze their properties.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.194-196
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• 2022

When electromagnetic wave transmitted from the radar antenna hits the target, a specific type of electric field is formed according to the electrical characteristics and appearance of the target, which is called an RCS pattern. There are various commercial programs that calculate the RCS of the target and plot the RCS pattern. For the analysis of large targets such as warships or ships, a program with a high frequency analysis method, which has a faster calculation speed than the low frequency analysis method is suitable. XGTD, a high-frequency analysis program, can quickly plot a two-dimensional RCS pattern for 360 degrees of a target, but a three-dimensional RCS pattern cannot be obtained. In this paper, it is proposed that a method of plotting two-dimensional RCS patterns of a target from various angles using XGTD, generating a three-dimensional RCS pattern using this, and converting it into a three-dimensional antenna pattern file.

• Progress in Medical Physics
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• v.25 no.1
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• pp.53-63
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• 2014

The objective of this study is to investigate the difference of ITV lengths and ITVs between 4DCT and Slow-CT images according to respiratory patterns using a respiratory motion phantom. The respiratory periods 1~4 s and target motion 1~3 cm were applied on each respiratory pattern. 4DCT and Slow-CT images were acquired for 3 times. 4DCT and Slow-CT ITVs were measured with contouring the target in the Eclipse RTP system. The measured ITV lenghts and ITVs in 4DCT and Slow-CT images were compared to the known values. For the ITV lengths and ITVs in the 4DCT, the difference of them were reduced as the respiratory period is longer and target motion is shorter. For the Slow-CT, there was same tendency with change in 4DCT ITV lengths and ITVs about target motion. However, the difference of ITV lengths and ITVs for the respiratory periods were the lowest in respiratory period 1 second and different slightly within respiratory period 2-4 seconds. According to the respiratory patterns, pattern A had the highest reproducibility. Pattern B, C and D were showed the difference similar to each other. However, for pattern E, the reproducibility was the lowest compared with other four patterns. The difference of ITV lengths and ITVs between Slow-CT and 4DCT was increased by increasing the respiratory periods and target motion for all respiratory patterns. When the difference of Slow-CT ITV lengths and ITVs were compared with that of 4DCT ITV lengths and ITVs, Slow-CT ITV lengths and ITVs were approximately 22 % smaller than 4DCT, and the representations of target were different in each pattern. In case of pattern A, B and C, length difference was 3 mm at S (superior) and I (inferior) direction, and the length difference of pattern D was 1.45 cm at only "I" direction whereas the length difference of pattern E was 5 mm longer in "S" direction than "I" direction. Therefore, the margin in SI directions should be determined by considering the respiratory patterns when the margin of Slow-CT is compensated for 4DCT ITV lengths. Afterward, we think that the result of this study will be useful to analyze the ITV lengths and ITVs from the CT images on the basis of the patient respiratory signals.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.539-542
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• 2009

해군에서는 소나를 이용하여 수중 표적을 효과적으로 탐색하기 위한 소나운용전술을 개발하기 위해 노력하고 있다. 효율적인 소나운용전술 개발을 위해서는 먼저 다양한 운영전술에 대한 효과도를 분석할 수 있는 시뮬레이션 시스템이 필요하다. 시뮬레이션 시스템은 해양환경 정보, 자함 정보, 소나 정보, 그리고 수중표적의 정보를 매개변수로 입력받아 운용전술에 대한 시뮬레이션을 수행하며, 시뮬레이션의 진행에 따른 다양한 정보를 제공할 수 있어야 한다. 본 연구에서는 다양한 환경에서 수중표적에 대한 함정의 최적 탐색 전략을 평가할 수 있는 탐색효과도 분석용 시뮬레이션 시스템을 설계 개발하였다. 시뮬레이션 시스템은 다양한 형태의 해양상태를 반영할 수 있도록 소나방정식 및 탐지확률곡선을 이용하여 개발되었으며, 표적의 실제적인 행동패턴을 고려하여 여러 가지 형태의 기동 패턴을 시스템에 묘사하였다. 개발된 시스템은 앞으로 수중표적에 대한 효율적인 소나운용전술을 개발하고 발전시키는데 유용하게 사용될 수 있을 것으로 판단된다.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.135-140
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• 2009

In this paper, we synthesized active sonar target signals based on highlights model, and then carried out target classification using the synthesized signals. If the target aspect angle is changed, the different signals are synthesized. To know the result, two different experiments are done. First, The classification results with respect to each aspect angle are shown. Second, the results in two group in aspect angle are acquired. Time domain feature extraction is done using matched filter and envelope detection. It shows the pattern of each highlights. Artificial neural networks and multi-class SVM are used for classifying target signals.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2
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• pp.30-37
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• 1994

Since the morden targets are of high speed and getting quiet in both active and passive mode, the necessities of developing advanced SONAR system capable of performing target motion analysis (TMA) and target classification are evident. In order to develop such a system, the scattering mechanism of complex bodies needs to be, some extent, fully understood and modeled. In this paper, MOving Spread Target(MOST) signal simulation model is presented and discussed. The model is based on the highlight distribution method, and simulates pulse elongation of spread target, doppler effect due to kinematics of the target as well as SONAR platform, and distribution target strength of each highlight point (HL) with directivity. The model can be used in developing and evaluating advanced SONAR system through system simulation, and can also be used in the development of target state estimation algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.629-632
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• 2004

수중 표적을 식별하기 위해서는 표적이 방사하는 소음의 특징을 미리 알고 있어야 한다. 소음의 특징은 스펙트럼상의 상이한 주파수나 특징적 패턴을 형성하는데 수중에서 표적을 구별하는 주요 성분이다. 이 논문에서는 이런 표적의 고유 식별 정보를 모델링하고 구축하는 수중 음향 분석 시스템을 설계, 구현하였다. 이로써 표적관련 음파 특징 정보를 수치화하고 체계적으로 구축해 정밀분석의 토대를 마련하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2753-2758
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• 2009

The Navy is trying to develop a sonar-operation strategy that efficiently searches for underwater targets. To develop an efficient sonar-operation strategy, a simulation system, which can analyze the efficiency of various operation strategies, is needed. The simulation executes the strategical operation by collecting information of sea environment, destroyer, sonar, and target. Also, it should be able to provide diverse information according to its progression. In this study, the simulation system that can evaluate and analyze the effectiveness of the search strategy for underwater targets in different environments was designed and developed. The simulation system was developed, utilizing the sonar equation and the lateral-range-curve, and it portrays many patterns of realistic movements of a target. This system will contribute to developing and improving efficient sonar-operation strategies to find underwater targets in the future.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.49-56
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• 2017

This paper proposes a method to improve the left right discrimination performance by eliminating the imaginary target based on the frequency features of the beam pattern for bow array. The beamwidth of the imaginary target is wider than that of the real target. If an azimuth axis is considered as a time axis, the real and the imaginary targets can be assumed as high and low frequencies, respectively. To eliminate the imaginary target which has a low frequency component, we design a cut-off frequency of the High Pass Filter (HPF) using the back-lobe imaginary beamwidth. The real target is estimated by eliminating the imaginary target by applying HPF to the entire power of the beamformer output. Computer simulations show that the proposed method can increase the left right discrimination performance above 8 dB on average.