• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.11
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• pp.1138-1144
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• 2009

The velocity and acceleration of the ground moving target can cause the target position to be displaced and defocused in the SAR image. In this paper, the displacement compensation scheme is presented to correct the displaced position and defocused moving target image in the DPCA based SAR-GMTI system. The influence of the ground moving target due to the velocity and acceleration is analyzed in range and azimuth directions, and its compensation method is presented with the simulation results. The performance of the proposed method is compared with respect to the estimated velocity and defocused quantity in both range and azimuth directions.

• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.277-280
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• 2008

무선 센서 네트워크에서 표적의 감시는 크게 표적의 탐지 및 추적과 표적의 식별로 나누어진다. 기존의 센서 노드에서의 신호 처리는 표적으로부터 수신된 신호의 에너지를 계산하여 표적의 존재 유무만을 기지국으로 전송하는 방법이 많이 사용되었다. 이런 기존의 방법은 표적의 감시를 위한 무선 센서 네트워크에서는 표적의 정보가 한정적이므로 적합하지 않다. 따라서 본 논문에서는 표적의 감시를 위한 무선 센서 네트워크에서 필요한 시간정보와 표적의 주파수 정보를 포함하는 센서 노드에서의 특징 추출 기법을 제안한다. 본 논문에서는 웨이블릿 변환을 이용하여 추출된 웨이블릿 상수에서 표적의 시간 정보와 잡음이 제거된 표적의 식별 정보를 추출함으로서 센서 노드에서 에너지 효율적인 신호처리를 구현하고 추출된 특징을 전송하여 통신에 소모되는 에너지를 줄이는 알고리듬을 제안한다.

• 한국항공운항학회:학술대회논문집
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• 2004.11a
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• pp.262-265
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• 2004

• 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 Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.195-202
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• 2005

An adaptive segmentation algorithm is used to efficiently target decisions in local non-stationary images. Until now, several adaptive approaches have been proposed as a method of segmentation. However, they can't be directly used for radar target detection because a radar signal has different characteristics from general images. Generally, a histogram of radar signal shows that targets have a relatively small number of frequency functions compared to the background and distribution of background, which have several shapes as the environment changes. In this paper, we propose an adaptive segmentation algorithm using a histogram chord which is a right-down line from maximum pick of frequency function. The proposed method provides thresholds which are optimum for several radar environments because the used chord for threshold search is not significantly effected by interference conditions. Simulation results show that the proposed method is superior to the traditional algorithms, global threshold method and distribution median method, with respect to detection performance.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.78-83
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• 2000

Passive sonar system is designed to classify the underwater targets by analyzing and comparing the various acoustic characteristics such as signal strength, bandwidth, number of tonals and relationship of tonals from the extracted tonals and frequency lines. First of all the precise detection and extraction of signal frequency lines is of particular importance for enhancing the reliability of target classification. But, the narrowband frequency lines which are the line formed in spectrogram by a tonal of constant frequency in each frame can be detected weakly or discontinuously because of the variation of signal strength and transmission loss in the sea. Also, it is very difficult to detect and extract precisely the signal frequency lines by the complexity of impulsive ambient noise and signal components. In this paper, the automatic detection and extraction method that can detect and extract the signal components of frequency tines precisely are proposed. The proposed method can be applied under the bad conditions with weak signal strength and high ambient noise. It is confirmed by the simulation using real underwater target data.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.300-304
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• 2017

In a cylindrical sonar, a conventional broadband energy detector has limitations in the separation of adjacent targets. In this paper, a broadband detection algorithm using cross-correlation is applied to the cylindrical sonar to improve the bearing resolution. The proposed algorithm uses split beamforming before broadband detection processing using cross-correlation to generate half beams. The time delay obtained from the peak of correlation between half beams is used to estimate the bearing of target. Simulations demonstrate the improved performance of the proposed algorithm against the conventional algorithm.

• Proceedings of the KAIS Fall Conference
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• 2006.11a
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• pp.242-244
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• 2006

본 논문에서는 레이더와 전자정보에서 획득한 방향정보 자료를 이용해서 전자파 정보를 융합하는 기술을 제시한다. 레이더에서 획득한 표적신호와 전자정보에서 획득한 정보신호를 융합하면 표적을 정확하게 확인할 수 있기 때문에 레이더의 탐지 오차율이 줄어들고 표적에 대한 상세 정보를 확보할 수 있어서 표적식별이나 목표물 선정에 쉽게 사용할 수 있다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.63-73
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• 2021

This paper presents a algorithm for automatic target recognition robust to the influence of the flame in order to track the target by EOTS(Electro-Optical Targeting System) equipped on UAV(Unmanned Aerial Vehicle) when there is aerial target or marine target with flame at the same time. The proposed method converts infrared images of targets and flames into a gradient vector field, and applies each gradient magnitude to a polynomial curve fitting technique to extract polynomial coefficients, and learns them in a shallow neural network model to automatically recognize targets and flames. The performance of the proposed technique was confirmed by utilizing the various infrared image database of the target and flame. Using this algorithm, it can be applied to areas where collision avoidance, forest fire detection, automatic detection and recognition of targets in the air and sea during automatic flight of unmanned aircraft.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.63-73
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• 2021

The radar operated to detect/track aircraft targets is divided into a search radar that operates while the antenna rotating device rotates for the purpose of detecting the target according to the mission characteristics, and a tracking radar that periodically steers and tracks a beam to the predicted position of the target. The tracking radar has a shorter target information acquisition preiod than the search radar. Due to this characteristic, the tracking accuracy is better than that of the search radar, but as the prediction error increases due to the speed error at the beginning of the tracking, there are many cases in which tracking fails at the beginning of tracking due to failure to perform beam steering normally. In this paper, in order to solve the above-mentioned problems, we propose an algorithm for improving the accuracy of track initiation using radial velocity measurements in addition to the position of the measured, and confirm the performance of the proposed algorithm by comparing with the two point differential algorithm