• Title/Summary/Keyword: signal intelligence

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An Analysis of Direction Finding Accuracy of ELINT System (TDOA 기법을 활용한 ELINT 장비의 방위탐지 정확도 분석)

  • Lim, Joong-Soo;Chae, Gyoo-Soo;Kim, Min-Nyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.11
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    • pp.3104-3109
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    • 2009
  • The technology of direction finding is very important to find the direction of emitters for ELINT(electronic intelligence) system. The principle of TDOA(time difference of arrival) is to receive an emitter signal with two antennas, measure the time difference between two antennas, and converse the time difference to direction difference. This technology can be used in broadband frequency system and make the system very simple because a phase-discriminator and a voltage comparator are not needed. For fine DF accuracy, high time resolution receiver and long basis line antennas are needed. The DF accuracy of noise added signals is simulated with different time

An Implementation of the Controller for Intelligent Process System using Neural Network (신경회로망을 이용한 지능형 가공 시스템 제어기 구현)

  • 김관형;강성인;이태오
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.6
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    • pp.1135-1141
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    • 2004
  • In this study, this system makes use of the analog infrared rays sensor and converts the feature of fish outline when sensor is operating with CPU(80C196KC). Then, after signal processing, this feature is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error back propagation is used as a teaming algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long when random initial weights are used, off-line teaming is induced to decrease the progress time.

Accident Prevention Technology at a Level Crossing (철도건널목 사고방지를 위한 방안 연구)

  • Cho, Bong-Kwan;Ryu, Sang-Hwan;Hwang, Hyeon-Chyeol;Jung, Jae-Il
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.12
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    • pp.2220-2227
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    • 2008
  • The safety equipments of railway level crossing which are installed at intersections between roads and railway lines prevent level crossing accidents by informing all of the vehicles and pedestrians of approaching trains. The intelligent safety system for level crossing which employs information and communication technology has been developed in USA and Japan, etc. But, in Korea, the relevant research has not been performed. In this paper, we analyze the cause of railway level crossing accidents and the inherent problem of the existing safety equipments. Based on analyzed results, we design the intelligent safety system which prevent collision between a train and a vehicle. This system displays train approaching information in real-time at roadside warning devices, informs approaching train of the detected obstacle in crossing areas, and is interconnected with traffic signal to empty the crossing area before train comes. Especially, we present the video based obstacle detection algorithm and verify its performance with prototype H/W since the abrupt obstacles in crossing areas are the main cause of level crossing accidents. We identify that the presented scheme detects both pedestrian and vehicle with good performance.

Development of a Bio-Signal Measuring System Based on D-F-M (D-F-M 기반의 생체신호측정기 개발)

  • Chai, Yong-Yoong;Hong, Dong-Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.4
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    • pp.897-902
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    • 2018
  • The purpose of this study is to develop a bioinformatic diagnostic system that diagnoses the patient 's health condition by using the output waveform generated by applying the impulse voltage of 13Hz to 7 body parts based on DFM (Diagnose Fure Funktionelle Medizine) theory. It is expected that the data acquired by the diagnostic system will be served as a device for diagnosing the status of the body organ as well as the mesenchymal tissue through inductive reasoning based on artificial intelligence. In this paper, we will limit the system to acquire and manage bio-signals.

The Optimal Controller Design of Buck-Boost Converter by using Adaptive Tabu Search Algorithm Based on State-Space Averaging Model

  • Pakdeeto, Jakkrit;Chanpittayagit, Rangsan;Areerak, Kongpan;Areerak, Kongpol
    • Journal of Electrical Engineering and Technology
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    • v.12 no.3
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    • pp.1146-1155
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    • 2017
  • Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.

Estimation of LOCA Break Size Using Cascaded Fuzzy Neural Networks

  • Choi, Geon Pil;Yoo, Kwae Hwan;Back, Ju Hyun;Na, Man Gyun
    • Nuclear Engineering and Technology
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    • v.49 no.3
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    • pp.495-503
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    • 2017
  • Operators of nuclear power plants may not be equipped with sufficient information during a loss-of-coolant accident (LOCA), which can be fatal, or they may not have sufficient time to analyze the information they do have, even if this information is adequate. It is not easy to predict the progression of LOCAs in nuclear power plants. Therefore, accurate information on the LOCA break position and size should be provided to efficiently manage the accident. In this paper, the LOCA break size is predicted using a cascaded fuzzy neural network (CFNN) model. The input data of the CFNN model are the time-integrated values of each measurement signal for an initial short-time interval after a reactor scram. The training of the CFNN model is accomplished by a hybrid method combined with a genetic algorithm and a least squares method. As a result, LOCA break size is estimated exactly by the proposed CFNN model.

Deep Learning Based Gray Image Generation from 3D LiDAR Reflection Intensity (딥러닝 기반 3차원 라이다의 반사율 세기 신호를 이용한 흑백 영상 생성 기법)

  • Kim, Hyun-Koo;Yoo, Kook-Yeol;Park, Ju H.;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.1
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    • pp.1-9
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    • 2019
  • In this paper, we propose a method of generating a 2D gray image from LiDAR 3D reflection intensity. The proposed method uses the Fully Convolutional Network (FCN) to generate the gray image from 2D reflection intensity which is projected from LiDAR 3D intensity. Both encoder and decoder of FCN are configured with several convolution blocks in the symmetric fashion. Each convolution block consists of a convolution layer with $3{\times}3$ filter, batch normalization layer and activation function. The performance of the proposed method architecture is empirically evaluated by varying depths of convolution blocks. The well-known KITTI data set for various scenarios is used for training and performance evaluation. The simulation results show that the proposed method produces the improvements of 8.56 dB in peak signal-to-noise ratio and 0.33 in structural similarity index measure compared with conventional interpolation methods such as inverse distance weighted and nearest neighbor. The proposed method can be possibly used as an assistance tool in the night-time driving system for autonomous vehicles.

Coordinated Millimeter Wave Beam Selection Using Fingerprint for Cellular-Connected Unmanned Aerial Vehicle

  • Moon, Sangmi;Kim, Hyeonsung;You, Young-Hwan;Kim, Cheol Hong;Hwang, Intae
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1929-1943
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    • 2021
  • Millimeter wave (mmWave) communication based on the wide bandwidth of >28 GHz is one of the key technologies for cellular-connected unmanned aerial vehicles (UAVs). The selection of mmWave beams in such cellular-connected UAVs is challenging and critical, especially when downlink transmissions toward aerial user equipment (UE) suffer from poor signal-to-interference-plus-noise ratio (SINR) more often than their terrestrial counterparts. This study proposed a coordinated mmWave beam selection scheme using fingerprint for cellular-connected UAV. The scheme comprises fingerprint database configuration and coordinated beam selection. In the fingerprint database configuration, the best beam index from the serving cell and interference beam indexes from neighboring cells are stored. In the coordinated beam selection, the best and interference beams are determined using the fingerprint database information instead of performing an exhaustive search, and the coordinated beam transmission improves the SINR for aerial UEs. System-level simulations assess the UAV effect based on the third-generation partnership project-new radio mmWave and UAV channel models. Simulation results show that the proposed scheme can reduce the overhead of exhaustive search and improve the SINR and spectral efficiency.

Design and Implementation of Green Coastal Lighting System for Entrance to Coastal Pier

  • Jae-Kyung Lee;Jae-Hong Yim
    • Journal of Navigation and Port Research
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    • v.47 no.2
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    • pp.85-92
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    • 2023
  • The hardware of an LED lighting control system for coastal lighting at coastal pier entrance consists of a power supply unit, an AVR control unit, a CLCD output unit, an LED control unit, a scenario selection switch unit, and an operation speed display unit. It is made of an 8-channel. The CPU used ATmega128 and the FET was used to control the current signal. To operate the CPU, DC 12V was converted to DC 5V using a regulator 7805. A heat sink was used to remove heat generated in the FET. By connecting the load LED module to the manufactured 8-channel LED lighting control system, the operation was confirmed through various production scenarios. In addition, a control system was designed to show the most suitable color for the atmosphere of the coastal pier according to the input value of temperature and illumination using a fuzzy control system. Computer simulation was then conducted. Results confirmed that fuzzy control did not need to store many data inputs due to characteristics of artificial intelligence and that it could efficiently represent many output values with simple fuzzy rules.

Beam Tracking Method Using Unscented Kalman Filter for UAV-Enabled NR MIMO-OFDM System with Hybrid Beamforming

  • Yuna, Sim;Seungseok, Sin;Jihun, Cho;Sangmi, Moon;Young-Hwan, You;Cheol Hong, Kim;Intae, Hwang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.1
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    • pp.280-294
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    • 2023
  • Unmanned aerial vehicles (UAVs) and millimeter-wave frequencies play key roles in supporting 5G wireless communication systems. They expand the field of wireless communication by increasing the data capacities of communication systems and supporting high data rates. However, short wavelengths, owing to the high millimeter-wave frequencies can cause problems, such as signal attenuation and path loss. To address these limitations, research on high directional beamforming technologies continue to garner interest. Furthermore, owing to the mobility of the UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. This study presents a beam tracking method based on the unscented Kalman filter using hybrid beamforming. The simulation results reveal that the proposed beam tracking scheme improves the overall performance in terms of the mean-squared error and spectral efficiency. In addition, by expanding analog beamforming to hybrid beamforming, the proposed algorithm can be used even in multi-user and multi-stream environments to increase data capacity, thereby increasing utilization in new-radio multiple-input multiple-output orthogonal frequency-division multiplexing systems.