• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.37-43
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• 2012

In this paper, we analysis wideband spectrum sensing with distance based weight combining for Cognitive Radio (CR) systems. CR systems is implemented the spectrum of the Primary User(PU) by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate (CFAR) algorithm for energy detection. The signal of PU is BPSK signal and the wireless channel between a PU and CR systems is modeled as Gaussian channel. From the simulation results, the wideband sensing with distance based and Distance based weight Combing (DWC) methods shows higher spectrum sensing performance than single CR user spectrum sensing.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.687-698
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• 2012

LADAR systems can rapidly acquire 3D point clouds by sampling the target surfaces using laser pulses. Such point clouds are widely used for diverse applications such as DSM/DTM generation, forest biomass estimation, target detection, wire avoidance and so on. Many kinds of LADAR systems have been developed with their respective purposes and applications. Particularly, Geiger mode imaging LADAR systems are increasingly utilized since they are energy efficient thank to extremely sensitive detectors incorporated into the systems. The purpose of this research is the performance assessment of a Geiger mode imaging LADAR system based on simulation with the real system parameters. We thus developed a simulation method of such a LADAR system by modeling its geometric, radiometric, optic and electronic aspects. Based on the simulation, we performed the performance assessment of a newly designed system to derive the outlier ratio and false alarm rate expected during its operation in almost real environment with reasonable system parameters. The proposed simulation and performance assessment method will be effectively utilized for system design and optimization, and test data generation.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.602-617
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• 2014

The performance of a cognitive radio network (CRN) solely depends on how precisely the secondary users can sense the presence or absence of primary users. The incorporation of a spatial false alarm makes deriving the probability of a correct decision a cumbersome task. Previous literature performed this task for the case of a received signal under a Normal probability density function case. In this paper we enhance the previous work, including the impact of carrier frequency, the gain of antennas on both sides, and antenna heights so as to observe the robustness against noise and interference and to make the correct decision of detection. Three small scale fading channels: Rayleigh, Normal, and Weibull were considered to get the real scenario of a CRN in an urban area. The incorporation of a maximal-ratio combining and selection combing with a variation of the number of received antennas have also been studied in order to achieve the correct decision of spectral sensing, so as to serve the cognitive users. Finally, we applied the above concept to a traffic model of the CRN, which we based on a two-dimensional state transition chain.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.85-94
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• 2019

Warhead and debris show the different micro-Doppler frequency shape in the spectrogram because of the different micro motion. So we can classify them using the micro-Doppler features. In this paper, we classified warhead and debris in the separation phase using CNN(Convolutional Neural Networks). For the input image of CNN, we used micro-Doppler spectrogram. In addition, to improve classification performance of warhead and debris, we applied the preprocessing using CA-CFAR to the micro-Doppler spectrogram. As a result, when the preprocessing of micro-Doppler spectrogram was used, classification performance is improved in all signal-to-noise ratio(SNR).

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.84.2-84.2
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• 2015

There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model (Lee et al. 2012) which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 1996 to 2014 using this model. Overall frequencies are 61.08% (C), 22.83% (M), and 5.44% (X). The maximum probabilities computed by the model are 99.9% (C), 89.39% (M), and 25.45% (X), respectively. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. For the critical success index widely used, the probability threshold values for contingency tables are 25% (C), 20% (M), and 4% (X). We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.15-0.83(C), 0.11-0.51(M), and 0.04-0.17(X), also depending on a lifetime of satellite. We expect that this study would provide a guideline to determine the probability threshold for space weather forecast.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.847-854
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• 2005

Since the propagation speed of the Internet worms is quite fast, worm detection in early propagation stage is very important for reducing the damage. Virus throttling technique, one of many early worm detection techniques, detects the Internet worm propagation by limiting the connection requests within a certain ratio.[6, 7] The typical throttling technique increases the possibility of false detection by treating destination IP addresses independently in their delay queue managements. In addition, it uses a simple decision strategy that determines a worn intrusion if the delay queue is overflown. This paper proposes a two dimensional delay queue management technique in which the sessions with the same destination IP are linked and thus a IP is not stored more than once. The virus throttling technique with the proposed delay queue management can reduce the possibility of false worm detection, compared with the typical throttling since the proposed technique never counts the number of a IP more than once when it chicks the length of delay queue. Moreover, this paper proposes a worm detection algorithm based on weighted average queue length for reducing worm detection time and the number of worm packets, without increasing the length of delay queue. Through deep experiments, it is verified that the proposed technique taking account of the length of past delay queue as well as current delay queue forecasts the worn propagation earlier than the typical iuぉ throttling techniques do.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.428-451
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• 2010

Traffic matrix-based anomaly detection and DDoS attacks detection in networks are research focus in the network security and traffic measurement community. In this paper, firstly, a new type of unidirectional flow called IF flow is proposed. Merits and features of IF flows are analyzed in detail and then two efficient methods are introduced in our DDoS attacks detection and evaluation scheme. The first method uses residual variance ratio to detect DDoS attacks after Recursive Least Square (RLS) filter is applied to predict IF flows. The second method uses generalized likelihood ratio (GLR) statistical test to detect DDoS attacks after a Kalman filter is applied to estimate IF flows. Based on the two complementary methods, an evaluation formula is proposed to assess the seriousness of current DDoS attacks on router ports. Furthermore, the sensitivity of three types of traffic (IF flow, input link and output link) to DDoS attacks is analyzed and compared. Experiments show that IF flow has more power to expose anomaly than the other two types of traffic. Finally, two proposed methods are compared in terms of detection rate, processing speed, etc., and also compared in detail with Principal Component Analysis (PCA) and Cumulative Sum (CUSUM) methods. The results demonstrate that adaptive filter methods have higher detection rate, lower false alarm rate and smaller detection lag time.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.75-84
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• 2003

Current techniques for road-traffic monitoring rely on sensors which have limited capabilities, are costly and disruptive to install. The use of video cameras coupled with computer vision techniques offers an attractive alternative to current sensors. Video based traffic monitoring systems are now being considered key points of advanced traffic management systems. In this paper, we propose the new method which extract the traffic information using video camera. The proposed method uses an adaptive updating scheme for background in order to reduce the false alarm rate due to various noises in images. also, the proposed extraction method of traffic information calculates the traffic volume ratio of vehicles passing through predefined detection area, which is defined by the length of profile occupied by cars over that of overall detection area. Then the ratio is used to define 8 different states of traffic and to interpret the state of vehicle flows. The proposed method is verified by an experiment using CCTV traffic data from urban area.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.172-182
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• 2014

In this paper, we investigate the fundamental performance limits of the cooperative sensing using energy detection by considering the unlimited number of sensing nodes. Although a lot of cognitive radio research so far proposed various uses of energy detection because of its simplicity, the performance limits of energy detection have not been studied when a large number of sensing nodes exist. First, we show that when the sensing nodes see the independent and identically distributed channel conditions, then as the number of sensing nodes N goes to infinity, the OR rule of hard decision achieves zero of false alarm Pf for any given target probability of detection $\bar{P_d}$ irrespective of the non-zero received primary user signal to noise ratio ${\gamma}$. Second, we show that under the same condition, when the AND rule of hard decision is used, there exists a lower bound of $P_f$. Interestingly, however, for given $\bar{P_d}$, $P_f$ goes to 1 as N goes to infinity. Third, we show that when the soft decision is used, there exists a way of achieving 100% utilization of secondary user, i.e., the sensing time overhead ratio goes to zero so does $P_f$.We verify our analyses by performing extensive simulations of the proposed unlimited cooperative sensing. Finally, we suggest a way of incorporating the unlimited cooperative sensing into a practical cellular system such as long term evolutionadvanced by exploiting the existing frame structure of absolute blank subframe to implement the in-band sensing.