• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.757-763
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• 2013

This study discusses the multiple knife-edge diffraction loss with the receiver and jammer located in the Seoul metropolitan northwestern region. The considered positioning and jamming signals are the GPS L1 C/A signal and several jamming signals such as the wideband Gaussian noise, matched spectrum, and continuous wave signals. To calculate the accurate diffraction effects, the 3-dimensional topography data at the Seoul metropolitan northwestern region was used.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.97-103
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• 2024

In this paper, the difference between the S-parameter and the characteristic impedance according to the structural change of the fine pitch coaxial socket was analyzed. A pitch of the probe pin was applied to 0.20mm, and ground pins of different conditions were placed on each of the five signal pins. Insertion loss and reflection loss were analyzed for the coaxial socket of normal structure and the two sockets of the proposed structure. In addition, the difference in characteristic impedance was analyzed using time domain reflectometry. Through the analysis, it was confirmed that the characteristic impedance was improved applying the new structures of the socket at the same pitch

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.610-621
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• 1998

In parameter design introduced by Taguchi, we analyze a signal-to-noise(SN) ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing SN ratios is presented, which can be used to several quality characteristics simultaneously in parameter design. To develop such multivariate SN ratios, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• Journal of Aerospace System Engineering
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• v.4 no.3
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• pp.17-23
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• 2010

GPS sensors provide accurate position and velocity of moving vehicles. However, GPS is weak at intermittent signal loss and large position error. Combination with INS improves the GPS position accuracy during the GPS signal loss. In this paper, a fusion filter using GPS and INS is developed and its perfomance is analyzed with RC car and RC airplane experiments.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.6
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• pp.457-463
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• 2018

This paper compares the results of ${\Sigma}{\Delta}-STAP$ applied to actual radar test data and simulation data. The radar received a target signal from a virtual target generator and the clutter signal from a signal generator in an anechoic chamber. The simulation data were generated from ideal baseband radar signal modeling using the same parameter as that for the test radar. The ${\Sigma}{\Delta}-STAP$ results of the test and simulation data are similar in terms of the target signal shape and noise level. The SINR(Signal-to-Interfrence-plus-Noise Ratio) loss also had similar aspects, but the simulation result shows 1~2 dB higher SINR loss than the test result. This result verified that the simulation data can be a reasonable alternative test data when the ${\Sigma}{\Delta}-STAP$ is applied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1755-1777
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• 2022

The development of wireless communication technology has led to the underutilization of radio spectra. To address this limitation, an intelligent cognitive radio network was developed. Specific emitter identification (SEI) is a key technology in this network. However, in realistic non-cooperative scenarios, the system may detect signal classes beyond those in the training database, and only a few labeled signal samples are available for network training, both of which deteriorate identification performance. To overcome these challenges, a meta-learning-based open-set identification system is proposed for SEI. First, the received signals were pre-processed using bi-spectral analysis and a Radon transform to obtain signal representation vectors, which were then fed into an open-set SEI network. This network consisted of a deep feature extractor and an intrinsic feature memorizer that can detect signals of unknown classes and classify signals of different known classes. The training loss functions and the procedures of the open-set SEI network were then designed for parameter optimization. Considering the few-shot problems of open-set SEI, meta-training loss functions and meta-training procedures that require only a few labeled signal samples were further developed for open-set SEI network training. The experimental results demonstrate that this approach outperforms other state-of-the-art SEI methods in open-set scenarios. In addition, excellent open-set SEI performance was achieved using at least 50 training signal samples, and effective operation in low signal-to-noise ratio (SNR) environments was demonstrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2338-2356
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• 2013

In cognitive radio networks, acquiring the position information of the primary user is critical to the communication of the secondary user. Localization of primary users can help improve the efficiency with which the spectrum is reused, because the information can be used to avoid harmful interference to the network while simultaneity is exploited to improve the spectrum utilization. Despite its inherent inaccuracy, received signal strength based on range has been used as the standard tool for distance measurements in the location detection process. Most previous works have employed the path-loss propagation model with a fixed value of the path loss exponent. However, in actual environments, the path loss exponent for each channel is different. Moreover, due to the complexity of the radio channel, when the number of channel increases, a larger number of RSS measurements are needed, and this results in additional energy consumption. In this paper, to overcome this problem, we propose using the Bayesian compressive sensing method with a calibrated path loss exponent to improve the performance of the PU localization method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.247-256
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• 2021

In this paper, we propose a packet loss concealment (PLC) algorithm using pitch harmonic motion prediction and adaptive signal amplitude prediction and. The spectral motion prediction method divides the spectral motion of the previous usable frame into predetermined sub-bands to predict and restore the motion of the lost signal. In the proposed algorithm, the speech signal is classified into voiced and unvoiced sounds. In the case of voiced sounds, it is further divided into pitch harmonics using the pitch frequency to predict and restore the pitch harmonic motion of the lost frame, and for the unvoiced sound, the lost frame is restored using the spectral motion prediction method. When the continuous loss of speech frames occurs, a method of adjusting the gain using the least mean square (LMS) predictor is proposed. The performance of the proposed algorithm was evaluated through the objective evaluation method, PESQ (Perceptual Evaluation of Speech Quality) and was showed MOS 0.1 improvement over the conventional method.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.1
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• pp.9-14
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• 2014

The path loss data was re-calculated according to the distance between the base station and a mobile station in the mobile telecommunications network. In this paper, the averaged path loss data was plotted with the conventional path loss models(free space, plane earth, Hata model ${\ldots}$). The standard deviations for the 2 Km, 1 Km, 0.5 Km-interval averaged path loss were 2.29 dB, 3.39 dB, 4.75 dB, respectively. Additionally, the derivative values for the 2 Km, 1 Km, 0.5 Km-interval averaged path loss were evaluated to find the positions with more than 1 times or 2times of the standard deviation. The situations with the sharply fluctuated path loss were calculated to 5 positions in the 2 Km interval, to 7 positions in the 1 Km interval, to 19 positions in the 0.5 Km interval, respectively. And, the exact distances between the base station and a mobile station were found with the sharply fluctuated path loss.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.117-120
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• 2001

Synthetic aperture radar (SAR) is a promising active remote sensing technique to obtain large terrain information of the earth in all-weather conditions. SAR is useful in many applications, including terrain mapping and geographic information system (GIS), which use SAR display images. Usually, these applications need the enormous data storage because they deal with wide terrain images with high resolution. So, compression technique is a useful approach to deal with SAR display images with limited storage. Because there is some indispensable data loss through the conversion of a complex SAR image to a display image, some applications, which need high-resolution images, cannot tolerate more data loss during compression. Therefore, lossless compression is appropriate to these applications. In this paper, we propose a novel lossless compression technique for a SAR display image using one-step predictor and block arithmetic coding.