• Title/Summary/Keyword: 표적 패턴

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Beamforming Method for Target Range Estimation Using Near Field Shading Function (근거리 쉐이딩 함수를 이용한 표적 거리 추정 빔형성 기법)

  • Choi, Joo-Pyoung;Lee, Won-Cheol
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.7
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    • pp.350-356
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    • 2008
  • In this paper, we propose shading functions to the appropriate focused beamforming for near-field target estimation. This near field shading functions are based on Chebychev and Manning windows. In order to obtain the optimum sensor weighting values with the help of the proposed shading technique, we assume that the sensor positions associated to the non-uniformly distributed array are precisely known. We calculate a series of sensor weighting values from the FFT operation of given shading functions in time domain. By applying the shading weights on the sensor array, we can see that the level of sidelobe becomes diminished and the performance of estimating range and azimuth gets improved. In addition, we propose a non-uniform structure in terms of frequency bands, which may minimize the attenuation of incoming signals.

A Location Management Scheme using HLR Agent and Caching (HLR 에이전트와 캐쉬 스킴을 이용한 위치 관리 기법)

  • 최문석;한기준
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.04a
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    • pp.466-468
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    • 2002
  • 본 논문에서는 가상의 HLR agent database를 이용해서 다양한 CM을 가지는 단말들에 대해 적용할 수 있는 위치관리 기법을 제안한다. 기존에 제안된 방법들은 단말의 CMR을 특정범위로 제한하고 있다. 표적으로 AS(Anchor Strategy)는 CMR이 낮을 경우 위치등록 용을, caching은 CMR이 높을 경우 호 설정 비용을 줄이는 기법이다. 그러나 현실적으로는 단말의 이동과 호 수신 패턴은 일정치 않다. 기존 기법과 본 논문에서 제안하는 기법간에 성능평가를 위해 다양한 CMR을 가지는 단말들에 대한 시뮬레이션을 수행한 결과, 제안기법은 데이터베이스 접근비용이 다소 증가하지만 전체적으로 15%~20%의 성능향상을 가져올 수 있었다.

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Influence of the Geoacoustic Parameters of Seabed Appearing in the Broadband Interference Pattern by Moving Targets (이동 표적에 의한 광대역 간섭패턴의 지음향 인자 영향)

  • Hahn, Joo-Young;Lee, Hyeong-Uk;Lee, Bong-Ki
    • Journal of the Korea Institute of Military Science and Technology
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    • v.10 no.3
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    • pp.43-50
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    • 2007
  • A range-frequency interference pattern is analyzed in the course of the propagation of ship noise in shallow water. It has been shown to exhibit striated bands of intensity maxima and minima in the spectrogram. The slope of the striations is an invariant of the modal interference and is described by a waveguide invariant parameter $\beta$. It turns out that this interference pattern is useful for identifying the physical properties of the waveguide such as seabed properties. In this article, the interference pattern is analyzed using image processing techniques to produce the distribution of the beta and the effects of sediment types and geoacoustic parameters on beta distribution are examined and characterized by moments of the distributions.

A Simulator Development for Determining the Sonar Sensor Configuration of Unmanned Underwater Vehicles Based on a Hold-at-Risk Scenario (위험제어 시나리오 기반의 무인잠수정 소나 센서 배열 선정을 위한 시뮬레이터 개발)

  • Shin, Myoungin;Lee, Jinho;Hong, Wooyoung;Kim, Woo Shik;Bae, Hoseuk;Cho, Hyunjin
    • Journal of the Korea Society for Simulation
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    • v.29 no.2
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    • pp.21-33
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    • 2020
  • This study develops a simulator for determining the sonar sensor configuration of unmanned underwater vehicles (UUVs) based on a scenario, in order for UUVs to conduct an effective anti-submarine warfare (ASW). First, we analyze the missions and operational concepts of UUVs in the field of ASW, and then select a Hold-at-Risk scenario as the one with the highest priority. Next, for modeling the components of a simulator, the motion, acoustic characteristic, and environment condition of the platforms (UUV and target submarine) are specified. Especially, based on the beam pattern of each sonar configuration considered in this paper, the passive sonar equation is used to verify target detection, and we further estimate the azimuth and elevation of the target using amplitude and phase of the received signal, respectively. The simulation results show the performance tendency depending on the sonar sensor configurations of a UUV, and the simulator provides a high applicability under various scenarios.

Monopulse Secondary Surveillance Radar Antenna with Sum/Difference/SLS Channels (합/차/부엽 억제 채널을 갖는 모노펄스 보조 감시 레이더(용) 안테나)

  • Choi, Jong-Hwan;Chae, Hee-Duck;Park, Jong-Kuk;Na, Hyung-Gi
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.7
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    • pp.720-728
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    • 2011
  • In this paper, development of the monopulse secondary surveillance radar antenna which can be used for IFF system is presented. This antenna that is passive linear array is comprised of the row-feeder and several array-elements. The row-feeder provides sum, different and SLS(Sidelobe Supression) channels which are optimized the distribution of the power and phase ratio. The azimuthe sidelobe level of the sum channel beam pattern is -20 dBc or less. The SLS channel covers the sidelobe of the sum-chanel in the whole azimuth angle range. And the difference channel is used to perform the mono-pulse function, improves the detection accuracy in the azimuth direction. Meanwhile, the arrayelement makes shaped beam in the elevation angle, in order to eliminate the clutter and multipath effects from the ground. Performance of the antenna developed is verified by the measurement of S-parameters and far-field beam pattern, and satisfies all of the development specifications well.

Three-dimensional Distortion-tolerant Object Recognition using Computational Integral Imaging and Statistical Pattern Analysis (집적 영상의 복원과 통계적 패턴분석을 이용한 왜곡에 강인한 3차원 물체 인식)

  • Yeom, Seok-Won;Lee, Dong-Su;Son, Jung-Young;Kim, Shin-Hwan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.10B
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    • pp.1111-1116
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    • 2009
  • In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.

A Simplified Horizontal Maneuvering Model of a RIB-Type Target Ship (RIB형 표적정의 수평면 조종운동 간략모델)

  • Yoon, Hyeon-Kyu;Yeo, Dong-Jin;Fang, Tae-Hyun;Yoon, Kun-Hang;Lee, Chang-Min
    • Journal of the Society of Naval Architects of Korea
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    • v.44 no.6
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    • pp.572-578
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    • 2007
  • A Rigid Inflatable Boat (RIB) is now widely used for commercial and military purpose. In this paper, it is supposed that seven-meter-class RIB be used as an unmanned target ship for naval training. In order to develop many tactical maneuvering patterns of a target ship, a simple horizontal maneuvering model of a RIB is needed. Therefore, models of speed and yaw rate are constructed as the first-order differential equations based on Lewandowski#s empirical formula for steady turning circle diameter of a conventional planning hull. Some parameters in the models are determined using the results of sea trial tests. Finally, proposed models are validated through the comparison of the simulation result with the sea trial result for a specific scenario. Even though a simple model does not represent the horizontal motion of a RIB precisely, however, it can be used enough to develop tactical trajectory patterns.

Three Stage Neural Networks for Direction of Arrival Estimation (도래각 추정을 위한 3단계 인공신경망 알고리듬)

  • Park, Sun-bae;Yoo, Do-sik
    • Journal of Advanced Navigation Technology
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    • v.24 no.1
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    • pp.47-52
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    • 2020
  • Direction of arrival (DoA) estimation is a scheme of estimating the directions of targets by analyzing signals generated or reflected from the targets and is used in various fields. Artificial neural networks (ANN) is a field of machine learning that mimics the neural network of living organisms. They show good performance in pattern recognition. Although researches has been using ANNs to estimate the DoAs, there are limitationsin dealing with variations of the signal-to-noise ratio (SNR) of the target signals. In this paper, we propose a three-stage ANN algorithm for DoA estimation. The proposed algorithm can minimize the performance reduction by applying the model trained in a single SNR environment to various environments through a 'noise reduction process'. Furthermore, the scheme reduces the difficulty in learning and maintains efficiency in estimation, by employing a process of DoA shift. We compare the performance of the proposed algorithm with Cramer-Rao bound (CRB) and the performances of existing subspace-based algorithms and show that the proposed scheme exhibits better performance than other schemes in some severe environments such as low SNR environments or situations in which targets are located very close to each other.

Multi-target Classification Method Based on Adaboost and Radial Basis Function (아이다부스트(Adaboost)와 원형기반함수를 이용한 다중표적 분류 기법)

  • Kim, Jae-Hyup;Jang, Kyung-Hyun;Lee, Jun-Haeng;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.3
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    • pp.22-28
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    • 2010
  • Adaboost is well known for a representative learner as one of the kernel methods. Adaboost which is based on the statistical learning theory shows good generalization performance and has been applied to various pattern recognition problems. However, Adaboost is basically to deal with a two-class classification problem, so we cannot solve directly a multi-class problem with Adaboost. One-Vs-All and Pair-Wise have been applied to solve the multi-class classification problem, which is one of the multi-class problems. The two methods above are ones of the output coding methods, a general approach for solving multi-class problem with multiple binary classifiers, which decomposes a complex multi-class problem into a set of binary problems and then reconstructs the outputs of binary classifiers for each binary problem. However, two methods cannot show good performance. In this paper, we propose the method to solve a multi-target classification problem by using radial basis function of Adaboost weak classifier.

The spatial-effect profile of visual attention in perception and memory (지각과 단기 기억 수준에 발현되는 주의 효과의 공간적 연장 패턴 비교)

  • Hyun, Joo-Seok
    • Korean Journal of Cognitive Science
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    • v.19 no.3
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    • pp.311-330
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    • 2008
  • The effect of spatial attention gradually decreases as a function of the distance between the locus of attention and a target. According to this hypothesis, we tested the spatial-effect profile of visual attention when it operates on perception and memory. Experiment 1 measured accuracy of discriminating the color of a simultaneously masked target after presenting a pre-cue to either at the target location or away from the target (perception-intensive task). Experiment 2 measured accuracy of recognizing the color of several items at and around the pre-cued location (memory-intensive task). In the perception-intensive condition, the accuracy gradually dropped as the distance between the cue and target location increases. However, in the memory-intensive condition, subjects remembered only the item at the cued location. This suggests spatial attention in a memory-intensive process would operate on object-based representations. Experiment 2 showed the object-based effect observed in Experiment 1 can be also present in perception under a special circumstance. The results indicate that spatial attention can operate on object-based representations in a memory-intensive process whereas it flexibly can operate either on location-based or object-based representations in a perception-intensive process.

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