• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.6
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• pp.733-738
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• 2014

In this paper, the performance of the narrowband channelized radiometer that have a short detection time and high time-resolution was verified based on the theoretical formula. According to the simulation result, the channelized radiometer showed 2.5 dB superior detection performance compared to the broadband radiometer, but is more sensitive to the effects of noise than the broadband radiometer. Also the signal-to-noise of a channelized radiometer was changed dramatically according to the hop rate and jitter effect, which is linearly decreased as the change of two parameters.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.1
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• pp.47-58
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• 2011

MTI filter is used to separate target signal from clutter in many radar signal processing. By suppressing clutter before CFAR detection, the detection performance can be improved. As a radar system designed, a design engineer generally takes averaged SNR and CNR into account and does not include the effect of MTI filter's frequency response. In practice, when the signals including clutter are pass through the filter, SNR is widely varying according to target velocity and CNR is also varying according to clutter center frequency and spectrum spreading. In this paper, we have derived the relationship between the MTI filter's frequency response and a target's velocity and a clutter's spectrum characteristics. With the variation of SNR and CNR at the filter output, the detection performance of CFAR has been analyzed by the simulation and has made certain of their influences on the performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.890-893
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• 2014

In this paper, we present a signal processing algorithm for a marine radar system, in which the evaluation of probability of collision as well as target detection and tracking are performed. Moreover, the digital signal processor that implements the algorithm is proposed. As simulation environment, a mechanically scanning antenna utilizing FMCW signal is used, conducting the beamforming operation with 1 degrees intervals. Test board consists of DSP chips and FPGA, which enable the implemented system to operate in real-time.

• ETRI Journal
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• v.38 no.1
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• pp.70-80
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• 2016

This paper addresses the problem of robust waveform design for distributed multiple-radar systems (DMRSs) based on low probability of intercept (LPI), where signal-to-interference-plus-noise ratio (SINR) and mutual information (MI) are utilized as the metrics for target detection and information extraction, respectively. Recognizing that a precise characterization of a target spectrum is impossible to capture in practice, we consider that a target spectrum lies in an uncertainty class bounded by known upper and lower bounds. Based on this model, robust waveform design approaches for the DMRS are developed based on LPI-SINR and LPI-MI criteria, where the total transmitting energy is minimized for a given system performance. Numerical results show the effectiveness of the proposed approaches.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.362-368
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• 2009

Electrical fires have been occurred continuously in spite of installing ELB. Therefore the concern with the electrical arc-fault that cause the fire has growing. This paper measured series arc fault currents by the method of arc generator test in UL standard 1699. The used analysis methods in this paper are three different ways using DWT(discrete wavelet transform) those are frequently used for the arc fault current signal analysis. The arc fault detection probability is 100 % by method using noise-energy/shoulder-duration ratio of approximation coefficient. As these results, the variation of noise-energy and shoulder-duration ratio of approximation coefficient are founded important factors for the analysis of arc fault.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.265-270
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• 2016

Extreme tropospheric anomalies such as typhoons or regional torrential rain can degrade positioning accuracy of the GPS signal. It becomes one of the main error terms affecting high-precision positioning solutions in network RTK. This paper proposed a detection algorithm to be used during atmospheric anomalies in order to detect the tropospheric irregularities that can degrade the quality of correction data due to network errors caused by inhomogeneous atmospheric conditions between multi-reference stations. It uses an atmospheric grid that consists of four meteorological stations and estimates the troposphere zenith total delay difference at a low performance point in an atmospheric grid. AWS (automatic weather station) meteorological data can be applied to the proposed tropospheric anomaly detection algorithm when there are different atmospheric conditions between the stations. The concept of probability density distribution of the delta troposphere slant delay was proposed for the threshold determination.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.45-48
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• 2006

This paper presents an approach to visual information based temporal indexing of video sequences. The objective of this work is the integration of an automatic face detection and a matching system for video indexing. The face detection is done using color information. The matching stage is based on the Principal Component Analysis (PCA) followed by the Minimax Probability Machine (MPM). Using PCA one feature vector is calculated for each face which is detected at the previous stage from the video sequence and MPM is applied to these feature vectors for matching with the training faces which are manually indexed after extracting from video sequences. The integration of the two stages gives good results. The rate of 86.3% correctly classified frames shows the efficiency of our system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.258-266
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• 2013

We propose adaptive detection algorithm to reduce a false alarm by considering the characteristics of the random noise on the detection system based on a seismic sensor. The proposed algorithm consists of the first step detection using kernel function and the second step detection using detection classes. Kernel function of the first step detection is obtained from the threshold of the Neyman-Pearon decision criterion using the probability density functions varied along the noise from the measured signal. The second step detector consists of 4 step detection class by calculating the occupancy time of the footstep using the first detected samples. In order to verify performance of the proposed algorithm, the detection of the footsteps using measured signal of targets (walking and running) are performed experimentally. The detection results are compared with a fixed threshold detector. The first step detection result has the high detection performance of 95% up to 10m area. Also, the false alarm probability is decreased from 40% to 20% when it is compared with the fixed threshold detector. By applying the detection class(second step detector), it is greatly reduced to less than 4%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.5 no.1
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• pp.34-39
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• 1980

This paper discribes a effect of Radio signals in Noise and Interference for the Communication systems and Generation of diffusion Noise from the Solid state Devices, and in Jection it to the Radio Reciving systems for probability of Signal Detection. The error performance depends on level of the Noise spectral density by Random processes between average signal energy. This experimental result are given by the performance of the correlation receiver for detecting Completely known signals in additive white Gaussian Noise.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.1
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• pp.43-62
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• 2017

Mobile pulse scanning Light Detection And Ranging (LIDAR) are essential components of intelligent vehicles capable of autonomous travel. Obstacle detection functions of autonomous vehicles require very low failure rates. With the increasing number of autonomous vehicles equipped with scanning LIDARs to detect and avoid obstacles and navigate safely through the environment, the probability of mutual interference becomes an important issue. The reception of foreign laser pulses can lead to problems such as ghost targets or a reduced signal-to-noise ratio. This paper will show the probability that any two scanning LIDARs will interfere mutually by considering spatial and temporal overlaps. We have conducted four experiments to investigate the occurrence of the mutual interference between scanning LIDARs. These four experimental results introduced the effects of mutual interference and indicated that the interference has spatial and temporal locality. It is hard to ignore consecutive mutual interference on the same line or the same angle because it is possible the real object not noise or error. It may make serious faults because the obstacle detection functions of autonomous vehicle rely on heavily the scanning LIDAR.