• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.87.3-88
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• 2017

한국천문연구원은 차세대소형위성 1호의 근적외선 영상분광기 NISS (Near-infrared Imaging Spectrometer for Star formation history) 탑재체를 개발하여 2017년 6월 30일에 최종 비행모델을 납품하였고, 이 발표는 탑재체 NISS 구조체의 비행모델 개발 결과를 보고한다. NISS는 0.9 - 2.5um (R~20) 근적외선 파장에서 관측을 해야 하기 때문에, 구조체의 배경잡음을 없애기 위해서 200K까지 passive cooling으로 냉각되며, H2RG 검출기는 소형 냉동기에 의해 약 88K에서 운영된다. NISS 구조체의 passive cooling을 효율적으로 수행하기 위해서 방열판, Kevlar 지지대, MLI, 표면제어용 필름 등을 조립하였고, 실제 지상 시험을 통해서 그 성능을 확인하였다. NISS 구조체는 최종 시스템 조립 과정에서 전자부 하네스 조립을 함께 수행했으며, 온도 모니터링 센서를 부착하고 소형 냉동기 피드백 온도를 반복 시험을 통해서 결정하였다. NISS 구조체는 미러 및 렌즈를 지지하는 광기계부를 함께 포함하기 때문에 발사 및 우주환경에서 광학 성능을 유지하기 위한 설계를 거쳐서 제작 되었으며, 최종 시스템 검교정 시험, 진동 및 열진공 시험을 통해서 그 성능을 확인하였다. NISS를 탑재한 차세대소형위성 1호는 2018년 상반기에 미국의 Falcon 9 발사체에 실려서 발사될 예정이다.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.97-107
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• 2017

In the field of automatic door, the infrared rays and microwave sensor are much used as the important components in charge of the motor's operation control of open and close through the incoming signal of object recognition. In case of existing system that the sensor of the infrared rays and microwave are applied to the automatic door, there are many malfunctions by the infrared rays and visible rays of the sun. Because the automatic doors are usually installed outside of building in state of exposure. The environmental change by temperature difference occurs the noise of object recognition detection signal. With this problem, the hardware fault that the detection sensor is unable to follow the object moving rapidly within detection area makes the sensing blind spot. This fault should be improved as soon as possible. Because It influences safety of passengers who use the automatic doors. This paper conducted an experiment to improve the detection area by installing extra ultrasonic sensor besides existing detection sensor. So, this paper realize the computing circuit and detection algorithm which can correctly and rapidly process the access route of objects moving fast and the location area of fixed obstacles by applying detection and advantages of ultrasonic signal to the automatic doors. With this, It is proved that the automatic door applying ultrasonic sensor is improved detection area of blind spot sensing through field test and improvement plan is proposed.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.78-86
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• 2017

In this paper, we propose hidden object detection system using parametric array based on acoustic signal that is harmless to human body. A transmit signal of the proposed detection system uses a high directive chirp signal generated from parametric array phenomenon, which uses technique to improve a signal to noise (SNR) of a received signal and a distance resolution trough the dechirp processing. The transmit sensor array is constructed as $8{\times}2$ and has a horizontal beam width of $7^{\circ}$ and vertical beam width of $26^{\circ}$. To verify the detection and visualization of the proposed system, a 2-axis driving control system based on linear stage was constructed, and A-scan, B-scan, and C-scan experiments was addressed for hidden object. From experimental results, we detected and visualized the hidden bronze plate and pipe by cloth and the visualized shapes was confirmed. Especially, the obtained errors was $0.015m^2$ for bronze plate, and $0.046m^2$ for pipe.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.611-624
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• 2012

'Gesture' is the most intuitive means of communication except the voice. Therefore, there are many researches for method that controls computer using gesture input to replace the keyboard or mouse. In these researches, the method of user detection and main body parts estimation is one of the very important process. in this paper, we propose user objects detection and main body parts estimation method on inaccurate depth information for pose estimation. we present user detection method using 2D and 3D depth information, so this method robust to changes in lighting and noise and 2D signal processing 1D signals, so mainly suitable for real-time and using the previous object information, so more accurate and robust. Also, we present main body parts estimation method using 2D contour information, 3D depth information, and tracking. The result of an experiment, proposed user detection method is more robust than only using 2D information method and exactly detect object on inaccurate depth information. Also, proposed main body parts estimation method overcome the disadvantage that can't detect main body parts in occlusion area only using 2D contour information and sensitive to changes in illumination or environment using color information.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.249-254
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• 2007

A mobile robot with various types of sensors and wireless camera is introduced. We show this mobile robot can detect objects well by combining the results of active sensors and image processing algorithm. First, to detect objects, active sensors such as infrared rays sensors and supersonic waves sensors are employed together and calculates the distance in real time between the object and the robot using sensor's output. The difference between the measured value and calculated value is less than 5%. We focus on how to detect a object region well using image processing algorithm because it gives robots the ability of working for human. This paper suggests effective visual detecting system for moving objects with specified color and motion information. The proposed method includes the object extraction and definition process which uses color transformation and AWUPC computation to decide the existence of moving object. Shape information and signature algorithm are used to segment the objects from background regardless of shape changes. We add weighing values to each results from sensors and the camera. Final results are combined to only one value which represents the probability of an object in the limited distance. Sensor fusion technique improves the detection rate at least 7% higher than the technique using individual sensor.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.471-482
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• 2016

This paper presents an extraction method for water body which uses block-based image partitioning and extension of water body boundaries to improve the performance of supervised classification for water body extraction. The Mahalanobis distance image is created by computing the spectral information of Normalized Difference Water Index (NDWI) and Near Infrared (NIR) band images over a training site within the water body in order to extract an initial water body area. To reduce the effect of noise contained in the Mahalanobis distance image, we apply mean curvature diffusion to the image, which controls diffusion coefficients based on connectivity strength between adjacent pixels and then extract the initial water body area. After partitioning the extracted water body image into the non-overlapping blocks of same size, we update the water body area using the information of water body belonging to water body boundaries. The update is performed repeatedly under the condition that the statistical distance between water body area belonging to water body boundaries and the training site is not greater than a threshold value. The accuracy assessment of the proposed algorithm was tested using KOMPSAT-2 images for the various block sizes between $11{\times}11$ and $19{\times}19$. The overall accuracy and Kappa coefficient of the algorithm varied from 99.47% to 99.53% and from 95.07% to 95.80%, respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.414-423
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• 2020

In this paper, we propose a Dilated Convolution Gate Linear Unit (DCGLU) to mitigate the lack of sparsity and small receptive field problems caused by the segmentation map extraction process in sound event detection with weak labels. In the advent of deep learning framework, segmentation map extraction approaches have shown improved performance in noisy environments. However, these methods are forced to maintain the size of the feature map to extract the segmentation map as the model would be constructed without a pooling operation. As a result, the performance of these methods is deteriorated with a lack of sparsity and a small receptive field. To mitigate these problems, we utilize GLU to control the flow of information and Dilated Convolutional Neural Networks (DCNNs) to increase the receptive field without additional learning parameters. For the performance evaluation, we employ a URBAN-SED and self-organized bird sound dataset. The relevant experiments show that our proposed DCGLU model outperforms over other baselines. In particular, our method is shown to exhibit robustness against nature sound noises with three Signal to Noise Ratio (SNR) levels (20 dB, 10 dB and 0 dB).

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.26-36
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• 2014

The needs of active phased arrays antenna system is getting more increased for IMT-Advanced system efficiency. The active phased array structure consists of lots of small transceivers and radiation elements to increase system efficiency. The minimized module of high efficiency transceiver is key for system implementation. The power amplifier of transmitter decides efficiency of base-station. In this paper, we design and implement minimized module of high efficiency transceiver for IMT-Advanced active phased array system. The temperature compensation circuit of transceiver reduces gain error and the analog pre-distorter of linearizer reduces implemented size. For minimal size and high efficiency, the implented power amplifier consist of GaN MMIC Doherty structure. The size of implemented module is $40mm{\times}90mm{\times}50mm$ and output power is 47.65 dBm at LTE band 7. The efficiency of power amplifier is 40.7% efficiency and ACLR compensation of linearizer is above 12dB at operating power level, 37dBm. The noise figure of transceiver is under 1.28 dB and amplitude error and phase error on 6 bit control is 0.38 dB and 2.77 degree respectively.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.97-104
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• 2017

In this paper, we designed and fabricated the multi band Transceiver Assembly(TCA) for the Multi Channel Synthetic Aperture Radar(MCSAR) containing C-band, X-band, Ku-band and we researched to verify electrical performance of TCA. The transceiver consists of transmitters, receivers, signal selection modules for each band, and stability oscillator, frequency synthesizer, controller, power distributor. The transceiver has a receive path selection and bandwidth selection functions in accordance with the operating mode. And the transceiver can transmit and receive all three bands simultaneously, each band has a bandwidth of up to 300 MHz. Final transmission output of transceiver for each band is over 20 dBm to be suitable for driving the T/R module. Receiver bandwidth is selected according to the required function and receiver gain has approximately C-band 52 dB, X-band 50 dB, Ku-band 60 dB, the maximum noise figure of Ku-band V polarization is 4.28 dB in the whole band H, V polarization. As a result of the electrical performance test, a multi-band TCA is satisfied the property requirements of the MCSAR.