• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.43-47
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• 2024

This paper introduces a phased-array single-channel transceiver beamformer IC built using 65nm CMOS technology, covering the 8-16 GHz range and targeting the X and Ku bands for radar and satellite communications. Each signal path in the IC features a low noise amplifier (LNA), power amplifier (PA), phase shifter (PS), and variable gain amplifier (VGA), which allow for phase and gain adjustments essential for beam steering and tapering control in typical beamforming systems. Test results show that the phase-compensated VGA offers a gain range of 15 dB with 0.25 dB increments and an RMS gain error of 0.27 dB. The active vector modulator phase shifter delivers a 360° phase range with 2.8125° steps and an RMS phase error of 3.5°.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.30-38
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• 2017

In this paper, we propose an underwater acoustic sensor fault detection method for passive sonar systems. In general, a passive sonar system displays processed results of array signals obtained from tens of the acoustic sensors as a two-dimensional image such as displays for broadband or narrowband analysis. Since detection result display in the operation software is to display the accumulated result through the array signal processing, it is difficult to determine the possibility where signal may be contaminated by the fault or failure of a single channel sensor. In this paper, accordingly, we propose a detection method based on the analysis of RMSCR (Root Mean Square Crossing-Rate), and the processing techniques for the faulty sensors are analyzed. In order to evaluate the performance of the proposed method, the precision of detecting fault sensors is measured by using signals acquired from real array being operated in several coastal areas. Besides, we compare performance of fault processing techniques. From the experiments, it is shown that the proposed method works well in underwater environments with high average RMS, and mute (set to zero) shows the best performance with regard to fault processing techniques.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.184-191
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• 2022

Underwater acoustic wave in shallow water is propagated through multipath that has a large delay spread causing Inter-Symbol Interference (ISI) and these characteristics deteriorate the performance in the communication system. In order to analyze the communication performance and investigate the correlation with multipath delay spread in a reverberant environment, an underwater acoustic communication experiment using Binary Phase-Shift Keying (BPSK) signals with symbol rates from 100 sym/s to 8000 sym/s was conducted in a 5 × 5 × 5 m³ water tank. The acoustic channels in a well-controlled tank environment had the characteristics of dense multipath delay spread due to multiple reflections from the interfaces and walls within the tank and showed the maximum excess delay of 40 ms or less, and the Root Mean Squared (RMS) delay spread of 8 ms or less. In this paper, the performances of Bit Error Rate (BER) and output Signal-to-Noise Ratio (SNR) were analyzed using four types of communication demodulation techniques. And the parameter, Symbol interval to Delay spread Ratio in reverberant environment (SDR_rev), which is the ratio of symbol interval to RMS delay spread in the reverberant environment is defined. Finally, the SDR_rev was compared to the BER and the output SNR. The results present the reference symbol rate in which high communication performance can be guaranteed.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.1
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• pp.42-55
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• 2008

To evaluate the accuracy of currents measured by HF radar in the coastal sea off Keum River estuary, we compared the facing radial vectors of two HF radars, and HF radar-derived currents with in-situ measurement currents. Principal component analysis was used to extract regression line and RMS deviation in the comparison. When two facing radar's radial vectors at the mid-point of baseline are compared, RMS deviation is 4.4 cm/s in winter and 5.4 cm/s in summer. When GDOP(Geometric Dilution of Precision) effect is corrected from the RMS deviations that is analyzed from the comparison between HF radar-derived and current-metermeasured currents, the error of velocity combined by HF radar-derived current is less than 5.1 cm/s in the stations having moderate GDOP values. These two results obtained from different method suggest that the lower limit of HF radar-derived current's accuracy is 5.4 cm/s in our study area. As mentioned in previous researches, RMS deviations become large in the stations located near the islands and increase as a function of mean distance from the radar site due to decrease of signal-to-noise level and the intersect angle of radial vectors. We found that an uncertain error bound of HF radar-derived current can be produced from the separation process of RMS deviations using GDOP value if GDOP value for each component is very close and RMS deviations obtained from current component comparison are also close. When the current measured in the stations having moderate GDOP values is separated into tidal and subtidal current, characteristics of tidal current ellipses analyzed from HF radar-derived current show a good agreement with those from current-meter-measured current, and time variation of subtidal current showed a response reflecting physical process driven by wind and density field.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.58-63
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• 1993

The charactistics of AE(Acoustic Emission) signal is related to cutting conditions, tool materials and tool geometry in metal cutting. The tool geometry change which is derived from tool wear affects the source of AE signal in machining process. The relationship between AE signal and tool wear was experimentally investigated. THe value of RMS(Root Mean Sequare) and Amplitude of AE signal were increased in tool wear condition. Also the high value of Count per Hit and Count vs. Frequency was observed in this condtion. As a result, tool wear can be effectively detected by AE signal during cutting operation.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.690-693
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• 1987

Base-line wandering and 60Hz noise in ECG are removed by linear phase FIR filter. The important problem in FIR filtering is to reduce the number of impulse response coefficients. It can be reduced by symmetrical impulse response. The ripple is improved by window function .omega.(n). And the determination of filter accuracy is proposed by PRD(percent rms difference) algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.150-156
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• 1996

Static variations of cutting forces are estimated using spindle motor current. Static sensitivity of spindle motor current is higher than feed motor current. The linear relationship between the cutting force and RMS value of the spindle motor current is obtained. Using cutting force estimation, tool overload in milling process can be well detected, and cutting force is regulated at a constant level by feedrate adaptive control.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.351-352
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• 2014

In this paper, series-arc detection algorithm for the consumer appliances is proposed. This algorithm uses varying frequency and RMS values at series-arc state. This is confirmed to emulate arc detecting with measuring current data.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.3
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• pp.221-228
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• 2016

In this paper, we introduce our simulation software for EEG signal accuracy improvement. Users can check and train own EEG signal accuracy using our simulation software. Subjects were shown emotional imagination condition with landscape photography and logical imagination condition with a mathematical problem to subject. We use that EEG signal data, and apply Independent Component Analysis algorithm for noise removal. So we can have beta waves(${\beta}$, 14-30Hz) data through Band Pass Filter. We extract feature using Root Mean Square algorithm and That features are classified through Support Vector Machine. The classification result is 78.21% before EEG signal accuracy improvement training. but after successive training, the result is 91.67%. So user can improve own EEG signal accuracy using our simulation software. And we are expecting efficient use of BCI system based EEG signal.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.142-148
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• 2016

Recently, human identification using various biological signals has been studied and human identification based on the gait has been actively studied. In this paper, we propose a human identification based on the EMG(Electromyography) signal of the thigh muscles that are used when walking. Various features such as RMS, MAV, VAR, WAMP, ZC, SSC, IEMG, MMAV1, MMAV2, MAVSLP, SSI, WL are extracted from EMG signal data and ANN(Artificial Neural Network) classifier is used for human identification. When we evaluated the recognition ratio per channel and features to select approptiate channels and features for human identification. The experimental results show that the rectus femoris, semitendinous, vastus lateralis are appropriate muscles for human identification and MAV, ZC, IEMG, MMAV1, MAVSLP are adaptable features for human identification. Experimental results also show that the average recognition ratio of method of using all channels and features is 99.7% and that of using selected 3 channels and 5 features is 96%. Therefore, we confirm that the EMG signal can be applied to gait based human identification and EMG signal based human identification using small number of adaptive muscles and features shows good performance.