• Geosystem Engineering
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• v.21 no.5
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• pp.251-261
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• 2018

With the urbanization in recent years, the power line interference noise in electromagnetic signal is increasing day by day, and has gradually become an unavoidable component of noises in magnetotelluric signal detection. Therefore, a kind of power line interference noise elimination method based on independent component analysis in wavelet domain for magnetotelluric signal is put forward in this paper. The method first uses wavelet decomposition to change single-channel signal into multi-channel signal, and then takes advantage of blind source separation principle of independent component analysis to eliminate power line interference noise. There is no need to choose the layer number of wavelet decomposition and the wavelet base of wavelet decomposition according to the observed signal. On the treatment effect, it is better than the previous power line interference removal method based on independent component analysis. Through the de-noising processing to actual magnetotelluric measuring data, it is shown that this method makes both the apparent resistivity curve near 50 Hz and the phase curve near 50 Hz become smoother and steadier than before processing, i.e., it effectively eliminates the power line interference noise.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.1
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• pp.39-45
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• 2011

In this paper, the design method of portable signal analysis system is proposed and the hardware module is implemented for operation of base stations based on a common platform for mobile WiMax. The new signal analysis method is implemented as two modules; a broadband RF module and a DSP based digital signal analysis module. The RF module performs the RF-IF down conversion and gain control. And the digital module measure the base staion signal. The differences of performance are insignificant in the experiment results performed through the comparison of other fixed-large system and proposed system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.342-349
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• 2019

We describe and anlayzes the methodology and implementation results of H / W configuration and signal characteristics analysis algorithm for analyzing equipment for analyzing OFDMA physical layer based on 802.16e. Recently, demand for signal analysis of instruments that analyze these signals with the development of digital communication signals is rapidly increasing. Accordingly, it is necessary to develop signal analysis equipment capable of analyzing characteristics of a broadband communication signal using a wideband digital signal processing module. In this paper, we have studied the basic theory of OFDMA in order to devise a device capable of analyzing characterisitcs of broadband communication signals. Second, the structure of OFDMA transmitter/receiver was examined. Third, a wideband digitizer was implemented. we design Wimax signal analysis algorithm based on OFDMA among broadband communication methods and propose Wimax physical layer analysis S/W implementation through I, Q signals. The IF downconverter used the receiver module and the LO generation module of the spectrum analyzer. Quantitative analysis result is obtained through the algorithm of Wimax signal analysis by I, Q data.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.55-66
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• 2021

In this paper, we propose a signal propagation modeling technique for generating a positioning fingerprint DB based on Long Term Evolution (LTE) signals. When a DB is created based on the location-based signal information collected in an urban area, gaps in the DB due to uncollected areas occur. The spatial interpolation method for filling the gaps has limitations. In addition, the existing gap filling technique through signal propagation modeling does not reflect the signal attenuation characteristics according to directions occurring in urban areas by considering only the signal attenuation characteristics according to distance. To solve this problem, this paper proposes a Deep Neural Network (DNN)-based signal propagation functionalization technique that considers distance and direction together. To verify the performance of this technique, an experiment was conducted in Seocho-gu, Seoul. Based on the acquired signals, signal propagation characteristics were modeled for each method, and Root Mean Squared Errors (RMSE) was calculated using the verification data to perform comparative analysis. As a result, it was shown that the proposed technique is improved by about 4.284 dBm compared to the existing signal propagation model. Through this, it can be confirmed that the DNN-based signal propagation model proposed in this paper is excellent in performance, and it is expected that the positioning performance will be improved based on the fingerprint DB generated through it.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.139-152
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• 2019

The design of new navigation signals is a key factor in building new satellite navigation systems and/or modernizing existing legacy systems. Navigation signal design involves selecting candidate groups and evaluating and analyzing their signal performances. This process can be easily performed through software simulation especially at the beginning of the development phase. The analytical signal performance analysis software introduced in this study is implemented based on equations between the signal design parameters of Radio Navigation Satellite Service (RNSS) and the navigation signal figures-of-merit (FoMs). Therefore, this study briefly summarizes the RNSS signal design parameters and FoMs before introducing the developed software. After that, we explain the operating sequence of the implemented software including the Graphical User Interface (GUI), and calculate the FoMs of an example scenario to verify the feasibility of the software operations.

• Near Infrared Analysis
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• v.1 no.2
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• pp.1-8
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• 2000

Using the net analyte signal, hybrid linear analysis was proposed to predict chemical concentration. In this paper, we select a sample from training set and apply orthogonal signal correction to obtain an improved pseudo unit spectrum for hybrid least analysis. using the mean spectrum of a calibration training set, we first show the calibration by hybrid least analysis is effective to the prediction of not only chemical concentrations but also physical property variables. Then, a pseudo unit spectrum from a training set is also tested with and without orthogonal signal correction. We use two data sets, one including five chemical concentrations and the other including ten physical property variables, to compare the performance of partial least squares and modified hybrid least analysis calibration methods. The results show that the hybrid least analysis with a selected training spectrum instead of well-measured pure spectrum still gives good performances, which is a little better than partial least squares.

• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.175-180
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• 2012

This paper presents a blind watermark detection scheme for an additive watermark embedding model. The proposed estimation-correlation-based watermark detector first estimates the embedded watermark by exploiting non-Gaussian of the real-world audio signal and the mutual independence between the host-signal and the embedded watermark and then a correlation-based detector is used to determine the presence or the absence of the watermark. For watermark estimation, blind source separation (BSS) based on independent component analysis (ICA) is used. Low watermark-to-signal ratio (WSR) is one of the limitations of blind detection with the additive embedding model. The proposed detector uses two-stage processing to improve the WSR at the blind detector; the first stage removes the audio spectrum from the watermarked audio signal using linear predictive (LP) filtering and the second stage uses the resulting residue from the LP filtering stage to estimate the embedded watermark using BSS based on ICA. Simulation results show that the proposed detector performs significantly better than existing estimation-correlationbased detection schemes.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.170-175
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• 2009

This paper introduces Zigbee based ubiquitous service. Most of ubiquitous services require the position information. Positioning algorithms utilize the transmission characteristics of the signal. Zigbee based positioning researches have been conducted mainly for the spatial factors inside the building. This paper proposes the possibility to consider the temporal factors of Zigbee signal and analyzes empirically the signal characteristics influenced according to the temporal factors as well as the spatial factors for ubiquitous services based on Zigbee sensor network.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1799-1802
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• 2002

This paper proposes an improved method for formant frequencies estimation based on the complex autocorrelation function of the speech signal. Instead of using the incoming signal as an input fur the LPC analysis, the analytic signal of the autocorrelation function of the speech signal is computed and itself used as an input for the LPC analysis. Due to the properties of the analytic signal, which occupies half of the bandwidth of the original signal, the required model order for the LPC analysis is halved. The accuracy of the proposed method in noisy environments is examined on five natural vowels. The effectiveness of the proposed method is shown by the estimated spectral shapes and the estimation errors of the formant frequencies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.283-289
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• 2012

Web-based physiological signal monitoring system can provide appropriate healthcare services to transmit bio-signal processing, analysis of bulk in medical centers. Therefore, we constructed a design of system to analyze effect of cardiac associated auricular acupuncture reflexology based on physiological signals. System to analyze effect cardiac associated auricular acupuncture reflexology, which carried out analysis and measurement of bio-signal to apply cardiac-related biometrics input in biometric image and voice signal. In addition, we also confirmed through statistical analysis actual home healthcare system to performance evaluation of system on subjects 20.