• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.78-84
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• 2022

In this paper, we propose a closed-form based 3D localization method in the presence of multiple signal sources. General localization methods such as TDOA, AOA, and FDOA can estimate a location when a single signal source exists. When there are multiple unknown signal sources, there is a limit in estimating the location. The proposed method calculates a cross-correlation vector of signals received by sensors having an array antenna, and estimates TDOA and AOA values from the cross-correlation values. Then, the coordinate transformation is performed using the position of the reference sensor. Then, the coordinate rotation is performed using the estimated AOA value for the transformed coordinates, and then the three-dimensional position of each emitter is estimated. The proposed method verifies its performance through computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.450-457
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• 2012

For orthogonal frequency-division multiplexing (OFDM) systems, we propose a blind channel estimation scheme based on non-redundant precoding. In the proposed scheme, a modified covariance matrix is first obtained by dividing the covariance matrix of the received signal vector by the precoding matrix element-by-element. Then, the channel vector is estimated as an eigenvector corresponding to the largest eigenvalue of the modified covariance matrix. The eigenvector can be obtained by power method with low computational complexity instead of the complicated eigenvalue decomposition. We analytically derive a mean square error (MSE) of the proposed channel estimation scheme and show that the analysis result coincides well with the simulation result. Also, simulation results show that the proposed scheme has better MSE and bit error rate (BER) performance than conventional channel estimation schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.611-619
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• 2016

Success in modern war depends on electronic warfare. Therefore, It is very important to identify the kind of Radar PRI modulations in a lot of Radar electromagnetic waves. In this paper, I propose an algorithm to identify Linear up Sliding PRI, Non-Linear up Sliding PRI and Linear Down Sliding PRI, Non-Linear Down Sliding PRI among many Radar pulses. We applied not only the TDOA(Time Difference Of Arrival) concept of Radar pulse signals incoming to antennas but also a rising and falling curve characteristics of those PRI's. After making a program by such algorithm, we input each 40 data to those PRI's identification programs and as a result, those programs fully processed the data in according to expectations. In the future, those programs can be applied to the ESM, ELINT system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.427-432
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• 2021

In this paper, we conduct performance analysis in automatic modulation classification of unknown communication signal to identify its modulation types based on deep neural network. The modulation classification performance was verified using time domain digital sample data of the modulated signal, frequency domain data to which FFT was applied, and time and frequency domain mixed data as neural network input data. For 11 types of analog and digitally modulated signals, the modulation classification performance was verified in various SNR environments ranging from -20 to 18 dB and reason for false classification was analyzed. In addition, by checking the learning speed according to the type of input data for neural network, proposed method is effective for constructing an practical automatic modulation recognition system that require a lot of time to learn.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.37-45
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• 2015

In modern electronic warfare systems, a demand on the more accurate estimation method based on TDOA and FDOA has been increased. TDOA/FDOA localization consists of two-stage procedures: the extraction of information from signals and the estimation of emitter location. Various algorithms based on CAF(complex ambiguity function), which is known as a basic method, has been presented in the area of extractions. When we extract TDOA and FDOA information using a conventional method based on the CAF algorithm from communication signals, considerably long integration time is required for the accurate position estimation of an unknown emitter far from sensors more than 300 km. Such long integration time yields huge amount of transmission data from sensors to a central processing unit, resulting in heavy computiational complexity. Therefore, we theoretically analyze the integration time for TDOA/FDOA information using CRLB and propose a two-stage global optimization algorithm which can minimize the transmission time and a computational complexity. The proposed method is compared with the conventional CAF-based algorithms in terms of a computational complexity and the CRLB to verify the estimation performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.88-96
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• 2014

In modern electronic warfare systems, the necessity of a more accurate estimation method based on non-AOA (arrival of angle) measurement, such as TDOA and FDOA, have been increased. The previous researches using single TDOA have been carried out in terms of not only the development of emitter location algorithms but also the enhancement of measurement accuracy. Recently, however, the combined TDOA/FDOA method is of considerable interest because it is able to estimate the velocity vector of a moving emitter and acquire a pair of TDOA and FDOA measurements from a single sensor pair. In this circumstance, it is needed to derive the required FDOA measurement accuracy in order that the TDOA/FDOA combined localization system outperforms the previous single TDOA localization systems. Therefore, we analyze the contribution of FDOA measurement accuracy to emitter location, then propose the criterion based on CRLB (Cramer-Rao lower bound). Simulations are included to examine the validity of the proposed criterion by using the Gauss-Newton algorithm.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.35-44
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• 2019

Individuals with problematic hypersexual behavior (PHB) evince the inability to control sexual impulses and arousal. Previous studies have identified that these characteristics are related to structural and functional changes in the brain region responsible for inhibitory functions. However, very little research has been conducted on the functional connectivity of these brain areas during the resting state in individuals with PHB. Therefore, this study used functional magnetic resonance imaging devices with the intention of identifying the deficit of the functional connectivity in the executive control network in individuals with PHB during the resting state. Magnetic resonance imaging data were obtained for 16 individuals with PHB and 19 normal controls with similar demographic characteristics. The areas related to the executive control network (LECN, RECN) were selected as the region of interest, and the correlation coefficient with time series signals between these areas was measured to identify the functional connectivity. Between groups analysis was also used. The results revealed a significant difference in the strength of the functional connectivity of the executive control network between the two groups. In other words, decreased functional connectivity was found between the superior/middle frontal gyrus and the caudate, and between the superior/middle frontal gyrus and the superior parietal gyrus/angular gyrus in individuals with PHB. In addition, these functional Connectivities related to the severity of hypersexual behavior. The findings of this study suggest that the inability to control sexual impulses and arousal in individuals with PHB might be related to the reduced functional connectivity of executive control circuits.