• 한국항행학회논문지
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• 제27권5호
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• pp.546-551
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• 2023

본 연구에서는 AESA 레이다의 근전계에서 송신/수신 모드에 대한 원전계 빔조향, 근전계 빔집속 등의 기능을 수행하기 위한 빔 조향 특성 측정 장치를 개발하였다. 빔조향 특성 측정장치는 구면형 근접전계 스캐너, 안테나 포지셔너, 근접전계 제어기, 네트워크 측정기, 레이다 제어시스템, 검증용 레이다 및 모의레이돔, AESA 레이다 등으로 구성된다. 개발한 시스템을 이용하여 AESA 레이다에 대한 레이돔장착전/후의 송/수신패턴특성을 측정하였고, 근접전계 측정 후 원전계로의 변환을 통해 빔패턴을 분석하였다. 그리고 레이다 안테나 장치의 보어사이트에러 를측정하였고, 모의 레이돔 장착 전후 메인로브가 동일하게 형성됨을 확인할 수 있었다.

• 한국군사과학기술학회지
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• 제21권5호
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• pp.583-590
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• 2018

Cross eye technique was proposed as an angle deception jamming technique against monopulse radars. Tracking radars use monopulse or conical scan methods for angle estimation of a target. Thus, if we verify deception performance of cross eye technique against a conical scan radar, efficient jamming systems can be developed to disturb both monopulse radars and conical scan radars. In this paper, we propose a mathematical model for a conical scan radar and a cross eye system. Using the proposed model, angular deception performance of the cross eye technique against conical scan radar is analyzed.

• 한국정보전자통신기술학회논문지
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• 제7권2호
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• pp.86-91
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• 2014

논문에서는 레이더 시스템에서 코히런트 집적과 비 코히런트 집적의 SNR 성능에 대해서 비교한다. 본 논문에서는 레이더 시스템에서 반사파와 전송파의 왜곡을 방지하기 위해 펄스파를 송신 파형으로 사용하였다. 본 논문에서는 포락선 검파기 앞에서 처리하는 코히런트 집적과 포락선 검파기 뒤에서 처리하는 비 코히런트 집적을 사용하여 목표물 탐지 거리를 추정하고 집적 방식에 따른 SNR 성능을 비교한다. 모의실험을 통해서 코히런트 집적과 비 코히런트 집적의 SNR 성능을 비교 분석하였다. 코히런트 집적이 비 코히런트 집적보다 SNR 성능이 우수함을 입증하였다.

• 수산해양기술연구
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• 제50권1호
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• pp.21-29
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• 2014

The dynamic information of radar and automatic identification system (AIS) for targets obtained from the traffic vessels operating in the north outer harbor and surrounding waters of Busan port, Korea. The target information was analyzed to investigate the potential collision risk resulting from the invalid true heading (HDT) information of AIS and the integration ambiguity in the graphic presentation of both tracked data sets for two systems. An integrated display system (IDS) for supporting the navigator of offshore fishing vessels was also developed to find possible maneuvering solutions for collision avoidance by comparing radar data with AIS data in real-time at sea. Consequently, the multiple functions of IDS can provide additional information that is potentially valuable for taking action to avoid the collision in offshore fishing vessels. However, the integration criteria of radar and AIS targets in the IDS must be carefully established to eliminate the fusion ambiguity in the graphic presentation of both AIS and radar symbols such as the one or two physical targets which are very close to each other.

• 한국군사과학기술학회지
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• 제22권4호
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• pp.475-483
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• 2019

Although radar target signatures(RTS), such as range profiles have played an important role for target recognition in the X-band radar, they would be less effective when a target is designed to have low radar cross section(RCS). Recently, a number of research groups have conducted the studies on the RTS in the VHF-band where such targets can be better detected than in the X-band. However, there is a lack of work carried out on the mathematical description of the VHF-band RTS. In this paper, chirplet decomposition is employed for modeling of the VHF-band RTS and its performance is compared with that of existing scattering center model generally used for the X-band. In addition, the discriminative signal analysis is performed by chirplet parameterization of range profiles from in an ISAR image. Because the chirplet decomposition takes long computation time, its fast form is further proposed for enhanced practicality.

• 대한임베디드공학회논문지
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• 제13권6호
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• pp.289-296
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• 2018

Drone detection in FMCW radar system needs complex techniques because a drone beat frequency is highly dynamic and unpredictable. Therefore, the current static signal processing algorithms cannot show appropriate detection accuracy. With dynamic signal fluctuation and environmental clutters, it can fail to detect a drone or make false detection. It affects to the radar system integrity and safety. Constant false alarm rate (CFAR), one of famous static signal process algorithm is effective for static environment. But for drone detection, it shows low detection accuracy. In this paper, we suggest neural network based FMCW radar system for detecting a drone. We use recurrent neural network (RNN) because it is the effective neural network for signal processing. In our FMCW radar system, one transmitter emits FMCW signal and four-way fixed receivers detect reflected drone beat frequency. The coordinate of the drone can be calculated with four receivers information by triangulation. Therefore, RNN only learns and inferences reflected drone beat frequency. It helps higher learning and detection accuracy. With several drone flight experiments, RNN shows false detection rate and detection accuracy as 21.1% and 96.4%, respectively.

• 한국전자파학회논문지
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• 제30권3호
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• pp.236-242
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• 2019

UWB(Ultra-WideBand)는 수 GHz 이상 광대역의 매우 짧은 신호를 이용하여 고속의 송수신이 가능한 기술로서, 최근 레이다 분야에 응용되고 있다. IR(Impulse Radio)-UWB 레이다의 경우, 높은 분해능으로 모션 인식 분야에도 적용되고 있다. 따라서, 본 논문에서는 IR-UWB 레이다를 이용한 모션 인식에 관한 연구를 진행하였다. 모션에 대한 데이터를 획득하기 위해 개발 환경을 구축하고, 성능 향상을 위한 신호처리 알고리즘을 구현하였다. 그리고 신호처리 결과를 바탕으로 모션의 특징 추출과 학습을 통해 성능을 검증하였다.

• 한국군사과학기술학회지
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• 제25권1호
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• pp.23-29
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• 2022

As the application field of radar is expanded and the bandwidth increases, the number of radar sensors operating at the same frequency is continuously increasing. In this paper, we propose a method of analyzing interference when two pulse doppler radars are operated at the same frequency with different waveform which are designed independently. In addition, we show that even for a previously designed LFM waveforms, the interference can be suppressed without affecting the performance by changing the sign of the frequency slope by increasing/decreasing, or by modulating the pulses by the different codes. The interference suppression by different slopes is more effective for similar waveform and the suppression by the codes increases as the number of pulses increases. We expect this result can be extended to the cases where multiple radars are operated at the same frequency.

• ETRI Journal
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• 제43권6호
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• pp.991-1003
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• 2021

Automatic modulation classification is essential in radar emitter identification. We propose a cascade classifier by combining a support vector machine (SVM) and convolutional neural network (CNN), considering that noise might be taken as radar signals. First, the SVM distinguishes noise signals by the main ridge slice feature of signals. Second, the complex envelope features of the predicted radar signals are extracted and placed into a designed CNN, where a modulation classification task is performed. Simulation results show that the SVM-CNN can effectively distinguish radar signals from noise. The overall probability of successful recognition (PSR) of modulation is 98.52% at 20 dB and 82.27% at -2 dB with low computation costs. Furthermore, we found that the accuracy of intermediate frequency estimation significantly affects the PSR. This study shows the possibility of training a classifier using complex envelope features. What the proposed CNN has learned can be interpreted as an equivalent matched filter consisting of a series of small filters that can provide different responses determined by envelope features.

• 한국군사과학기술학회지
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• 제16권3호
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• pp.365-372
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• 2013

The multibeam surveillance radar is a state-of-art of 3D radar technology. It applies the stacked beams realized by a digital beamformer. In this paper, a hybrid compensation technique on elevation angle errors for low elevation angle targets over the sea in multipath radar environments is proposed. The proposed method can be applied to stacked beam radars. Double null algorithm based on maximum likelihood method in 3-D beamspace domain works well unless the phase difference between the two rays(direct and specular path) is close to $0^{\circ}$ and the magnitude of reflection coefficient is close to 0. To overcome these problems, we propose a hybrid compensation technique which uses the selective double null algorithm and the beam-ratio compensation technique for low-elevation errors on a log scale. Results of computer simulation show that the proposed method outperform conventional monopulse method and double null algorithm only under various multipath environments.