• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.149-155
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• 2023

In urban areas it can be difficult to utilize global navigation satellite systems (GNSS) due to signal reflections and blockages. It is thus crucial to detect reflected or blocked signals because they lead to significant degradation of GNSS positioning accuracy. In a previous study, a classifier for global positioning system (GPS) signal reception conditions was developed using three features and the support vector machine (SVM) algorithm. However, this classifier had limitations in its classification performance. Therefore, in this study, we developed an improved machine learning based method of classifying GPS signal reception conditions by including an additional feature with the existing features. Furthermore, we applied various machine learning classification algorithms. As a result, when tested with datasets collected in different environments than the training environment, the classification accuracy improved by nine percentage points compared to the existing method, reaching up to 58%.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.530-532
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• 2005

Actually, it's very difficult to discriminate the transient on underground power cable system because of the reflected signal including many noises. Therefore, in this paper, a solution based on multiple scales correlation of the transient using SWT(Stationary Wavelet Transform) is presented. It's quick and straightforward. For applying all algorithms, we just use the signal captured in single end.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.450-456
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• 2016

STDR (sequence time domain reflectometry) to detect a cable fault using a pseudo noise sequence as a reference signal, and time correlation analysis between the reference signal and reflection signal is robust to noisy environments and can detect intermittent faults including open faults and short circuits. On the other hand, if the distance of the fault location is far away or the fault type is a soft fault, attenuation of the reflected signal becomes larger; hence the correlation coefficient in the STDR becomes smaller, which makes fault detection difficult and the measurement error larger. In addition, automation of the fault location by detection of phase and peak value becomes difficult. Therefore, to improve the cable fault detection of a conventional STDR, this paper proposes the algorithm in that the peak value of the correlation coefficient of the reference signal is detected, and a peak value of the correlation coefficient of the reflected signal is then detected after removing the reference signal. The performance of the proposed method was validated experimentally in low-voltage power cables. The performance evaluation showed that the proposed method can identify whether a fault occurred more accurately and can track the fault locations better than conventional STDR despite the signal attenuation. In addition, there was no error of an automatic fault type and its location by the detection of the phase and peak value through the elimination of the reference signal and normalization of the correlation coefficient.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.77-84
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• 2009

Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is applied to synthetic and field GPR data acquired over a buried pipe. The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a reference signal for pulse compression. For a pulse-compression filter, reference signal selection is an important issue, because as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is low. Analysis of the results obtained from simulated and field GPR data indicates a significant improvement in the GPR image, good discrimination between the target reflection and the ground surface reflection, and better performance with reliable separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.

• Journal of Advanced Navigation Technology
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• v.13 no.1
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• pp.34-40
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• 2009

The phase delay of output signal of APD(avalanche photo diode) caused by intensity of reflected light which comes from target. These difference of phase delay is an one of the main reason of measurement error, but there is no reasonable measurement meter and method to detect it. In this paper, to solve the problem, we propose and implement a method to measure the intensity of radiation. The method measures DC voltage which is proportional to the reflected intensity of radiation and come out from APD in receiver by realtime.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.28-33
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• 2017

In this paper, new signal model for bio-signal detection, i.e heart beat and respiration, using CW radar. Most research on this similar topic are based on the conventional signal model which is not correct in envisaging reflected signal from the human body. The system developed based on this conventional model can not predict exact performance of the system. So in this paper modified signal model for bio-radar is proposed and then simulation for detecting heartbeat and respiration signal in AWGN, multipath environment. The detection performance difference between two signal models are discussed.the modified

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.2
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• pp.115-124
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• 2015

A methodology is proposed to estimate a trajectory of a flying target and its velocity using the time and frequency analysis of the acoustic signal. The measurement of sound emitted from a flying acoustic source with a microphone above a ground shall receive both direct and ground-reflected sound waves. For certain frequency contents, the destructive interference happens in received signal waveform reflected path lengths are in multiple integers of direct path length. This phenomenon is referred to as the acoustical mirror effect and it can be observed in a spectrogram plot. The spectrogram of acoustic measurement for a flying vehicle measurement shows several orders of destructive interference curves. The first or second order of curve is used to find the best approximate path by using nonlinear least-square method. Simulated acoustic signal is generated for the condition of known geometric of a sensor and a source in flight. The estimation based on cepstrogram analysis provides more accurate estimate than spectrogram.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.64-71
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• 2017

In this paper, Kalman filter and RRWA algorithm are used to estimate the accurate target in IR-UWB (Impulse-Radio Ultra Wideband) radar system, which enables accurate location recognition of indoors and outdoors with low cost and low power consumption. In the signal reflected by the target, unnecessary signals exist in addition to the target signal. We have tried to remove unnecessary signals and to derive accurate target signals and improve performance. The location of the targets is estimated in real time with one transmitting antenna and one receiving antenna. The Kalman filter was used to remove the background noise and the RRWA algorithm was used to remove the reflected signal. In this paper, we think that it will be useful to study the accurate distance estimation and tracking in future target estimation.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.156-163
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• 2013

In this paper, we propose an algorithm for estimating media characteristics of sea water and subbottom multi-layers. The proposed algorithm for estimating reflection coefficients, uses a transmitted signal and reflected signal obtained from multiple layers of various shape and structure, and the algorithm is called Schur algorithm. The algorithm is efficient in estimating the reflection coefficients since it finds solution by converting the given inverse scattering problem into matrix factorization. To verify the proposed algorithm, we generate a transmit signal and reflected signal obtained from lattice filter model for sea water and subbottom of multi-level non-homogeneous layers, and then find that the proposed algorithm can estimate reflection coefficients efficiently.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.32-38
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• 2005

FBG sensors have been studied more actively than any other fiber optic sensor because of good multiplexing capabilities among many fiber optic sensors. The demodulation method of FBG sensors is based on the detection of wavelength shift of their sensor peaks and properties such as strain and temperature can be measured by detecting them. However, the signal stability of FBG sensors can be influenced by the strain gradient induced by structural geometry or cracks on the surface when FBG sensors are embedded into or attached on the structure. In this study, the signal characteristics of reflected spectra of FBG sensors under strain gradient were verified and the relations between the grating length of FBG sensors and the amount of strain gradient were investigated. From the experimental results, the recommended working range of FBG sensors under strain gradients was shown quantitatively with respect to grating lengths of them.