• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.385-390
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• 2006

This paper examines the sampling and jitter specifications and considerations for Global Navigation Satellite Systems (GNSS) software receivers. Software radio (SWR) technologies are being used in the implementation of communication receivers in general and GNSS receivers in particular. With the advent of new GPS signals, and a range of new Galileo and GLONASS signals soon becoming available, GNSS is an application where SWR and software-defined radio (SDR) are likely to have an impact. The sampling process is critical for SWR receivers, where it occurs as close to the antenna as possible. One way to achieve this is by BandPass Sampling (BPS), which is an undersampling technique that exploits aliasing to perform downconversion. BPS enables removal of the IF stage in the radio receiver. The sampling frequency is a very important factor since it influences both receiver performance and implementation efficiency. However, the design of BPS can result in degradation of Signal-to-Noise Ratio (SNR) due to the out-of-band noise being aliased. Important to the specification of both the ADC and its clocking Phase- Locked Loop (PLL) is jitter. Contributing to the system jitter are the aperture jitter of the sample-and-hold switch at the input of ADC and the sampling-clock jitter. Aperture jitter effects have usually been modeled as additive noise, based on a sinusoidal input signal, and limits the achievable Signal-to-Noise Ratio (SNR). Jitter in the sampled signal has several sources: phase noise in the Voltage-Controlled Oscillator (VCO) within the sampling PLL, jitter introduced by variations in the period of the frequency divider used in the sampling PLL and cross-talk from the lock line running parallel to signal lines. Jitter in the sampling process directly acts to degrade the noise floor and selectivity of receiver. Choosing an appropriate VCO for a SWR system is not as simple as finding one with right oscillator frequency. Similarly, it is important to specify the right jitter performance for the ADC. In this paper, the allowable sampling frequencies are calculated and analyzed for the multiple frequency BPS software radio GNSS receivers. The SNR degradation due to jitter in a BPSK system is calculated and required jitter standard deviation allowable for each GNSS band of interest is evaluated. Furthermore, in this paper we have investigated the sources of jitter and a basic jitter budget is calculated that could assist in the design of multiple frequency SWR GNSS receivers. We examine different ADCs and PLLs available in the market and compare known performance with the calculated budget. The results obtained are therefore directly applicable to SWR GNSS receiver design.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.88-97
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• 1995

The main purpose of this paper is to show the realizaability of the proposed highly effective direction finiding method which performs extremely well under the circumstances like low signal-to-noise ratio (S/N), very closely located signal sources, and so on. In order to achieve the purpose, the degree to which the proposed method is superior to the MUSIC(multiple signal classification) with respect to the S/N is discussed, and the result is analyzed in terms of the S/N and the number of sample data.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.1
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• pp.65-73
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• 2007

Pattern classification of single and multiple discharge sources was applied using a wavelet image signal method in which a feature extraction was applied using a hidden sub-image. A feature extracting method that used vertical and horizontal images using an MSD method was applied to an averaging process for the scale of pulses for the phase. A feature extracting process for the preprocessing of the input of a neural network was performed using an inverse transformation of the horizontal, vertical, and diagonal sub-images. A back propagation algorithm in a neural network was used to classify defective signals. An algorithm for wavelet image processing was developed. In addition, the defective signal was classified using the extracted value that was quantified for the input of a neural network.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.51-54
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• 2002

As digital systems continue to use components with faster edge rate and clock speeds, transmission of the digital information can take place many troubles. The increasing requirement for controlled impedance PCBs becomes both a critical success factor and a design challenge. Especially, the noise sources in digital system include the noise in power supply, ground and packaging due to simultaneous switching of signal, signal reflections and distortions on single and multiple transmission lines. This paper simulates the tracks controlled impedance with the test coupon. So, it can saves the design time and supports the economical PCB design.

• Journal of electromagnetic engineering and science
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• v.10 no.4
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• pp.250-255
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• 2010

This paper presents a non-contact measurement method of vital signal by the use of multiple-input multiple-output (MIMO) bio-radar system, configured with two antennas that are separated by a certain distance. The direction of arrival (DOA) estimation algorithm for coherent sources was applied to detect vital signals coming from different spatial angles. The proposed MIMO bio-radar system was composed of two identical transceivers sharing single VCO with a PLL. In order to verify the performance of the system, the DOA estimation experiment was completed with respect to the human target at angles varying between $-50^{\circ}$ and $50^{\circ}$ where the bio-radar system was placed at distances (corresponding to 50 cm and 95 cm) in front of a human target. The proposed MIMO bio-radar system can successfully find the direction of a human target.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1003-1008
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• 2001

In beamforming method, source positions are predicted by MUSIC (Multiple Signal Classification) power method and composite sound fields can then be decomposed into each partial field by beamforming, detenninistically without restriction of the distance between reference microphones and sources. However, reference microphone array shape is important in both MUSIC and beamforming method. Thus the present paper describes the effect of the reference microphone array shape.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.149-153
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• 1999

As VLSI technology advances rapidly, the operating frequency of digital systems becomes very fast. In such a high-speed system, there are many factors that threaten signal integrity. The noise sources in digital system include the noises in power supply, ground bounce and packaging media and distortions on single and multiple transmission lines. This paper will present a technology survey useful in the design of Gigabit interconnection systems. Some case studies have been constructed which show the lossy transmission line effect of skin effect. dielectric loss, with backplane connectors using the theoretical and practical conditions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.483-489
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• 2009

The Time Difference of Arrival (TDOA) algorithm is being used widely for identifying the location of a source emanating either electrical or acoustic signal. It's application areas will not be limited to identifying the source at a fixed location, for example the origin of an earthquake, but will also include the trajectory monitoring for a moving source equipped with a GPS sensor. Most of the TDOA algorithm uses time correlation technique to find the time delay between received signals, and therefore difficult to be used for identifying the location of multiple sources. In this paper a TDOA algorithm based on cross-spectrum is developed to find the trajectory of two sound sources with different frequencies. Although its application is limited to for the sources on a disk plane, but it can be applied for identifying the locations of more than two sources simultaneously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.12
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• pp.2303-2312
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• 1994

A high resolution algorithm is presented for resolving multiple narrowband plane waves that are incident on an equispaced linear array. To overcome the deleterious effects due to coherent sources, a number of noise-eigenvector-based approaches have been proposed for narrowband signal processing. For differing reasons, each f these methods provide a less than satisfactory resolution of the coherency problem. The proposed algorithm makes use of fundamental property possessed by those eigenvectors of the spatial covariance matrix that are associated with eigenvalues that are larger than the sensor noise level. This property is then used to solve the incoherent and coherent sources incident on an equispaced linear array. Simulation results are shown to illustrate the high resolution performance achieved with this new approach relative to that obtained with MUSIC and spatial smoothed MUSIC.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.687-690
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• 1999

Many high-resolution algorithms based on the eigen-decomposition analysis of observed covariance matrix, such as MVE, MUSIC, and EVM, have been proposed. However, the resolution of spectral estimates for these algorithms is severely degraded when Signal-to-Noise Ratio (SNR) is low and arrival angles of signal are close to each other. And EVM and MUSIC is powerful for the characteristic of SNR. But have the limitation that the number of signals presented is known. While MVE is bad the characteristic of SNR. In this study, we propose a modified MVE to enhance the resolution for Direction-Of-Arrival (DOA) estimation of underwater acoustic signal. This is to remove the limitation that existing algorithms should know the information for the number of signals. Because the algorithms founded on the eigen value estimate DOA with only the noise subspace, they have the high-resolution characteristic. And then, with the method reducing the effect of the signal subspace, we are to reduce the degradation because of complementary relationship between the signal subspace and the noise subspace. This paper, with using the simulation data, we have estimated the proposed algorithms, compared it with other high-resolution algorithms. The simulation results show that the modified MVE proposed is accurate and has a better resolution even though SNR is low, under the same condition.