• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.97-97
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• 2000

In this paper, a signal processing algorithm for software GPS receiver is proposed. The signal processor takes snapshot of the sampled If signal from the RF section of the GPS receiver. All the processing for code and carrier tracking and correlation are implemented using the digital signal processing techniques. In order to achieve fast code acquisition, correlation of the incoming GPS signal is performed using the FFT method, After code acquisition, to reduce the Doppler shift effect and increase the accuracy, the interpolation or the tracking are performed. The performance of the proposed processing algorithm is first evaluated using matlab/simulink. A signal acquisition board for sampling and logging GPS IF signal form the Mitel GPS RF chip set is constructed. In order to analyze the performance of the designed algorithm the experiments are performed and the results are analyzed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.7
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• pp.555-561
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• 2014

Acoustic Emission technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the bearing problems and wavelet transform is a powerful method to detect faults occurred on rotating machinery. However, exact method for AE signal is not developed yet for the rotating machinery diagnosis. Therefore, in this paper two methods which are processed by Hilbert transform and DET for feature extraction. In addition, we evaluate the classification performance with varying the parameter from 2 to 15 for feature selection DET, 0.01 to 1.0 for the RBF kernel function of SVR, and the proposed algorithm achieved 94 % classification of averaged accuracy with the parameter of the RBF 0.08, 12 feature selection.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.2
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• pp.251-254
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• 2014

In this paper, we studied a technique of extracting a Frequency Hopping(FH) signal for analysis using high-speed parallel processing structure. Unlike fixed frequency signal, FH signal is difficult to detect and analyze because FH systems use many random frequencies instead of a single carrier frequency. To solve this problem we designed a method that analyze FH signal using high-speed parallel processing. In order to apply parallel processing, we use CUDA using GPU and compare single processing with prarallel processing. As a result, using CUDA on a GPU is about 8.53 times faster than single processing.

• Proceedings of the KWS Conference
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• 1996.10a
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• Proceedings of the KSR Conference
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• 1999.05a
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• pp.143-150
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• 1999

The vibration signals of driving parts of electric train are distorted its signal patterns due to the impact components, which occurs when wheel passes rail joints. An elimination method of the impact components is investigated using adaptive signal processing technique in this study. The result shows that adaptive interference canceling method seems to be more effective than line enhancement technique. The application of adaptive interference canceling method to the signal measured at bogie shows that the extractions of the signals of driving parts of traction motor, reduction gear, and axle bearing are successful. Therefore, only the signals of bogie, which is the place to attach an accelerometer easily, is sufficient for the fault diagnosis and the safety evaluation of electric train. Also, adaptive interference canceling method can be applicable to evaluate the performance of vibration isolation between bogie and car body and to investigate the characteristics of indoor sound.

• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.817-826
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• 2001

In this paper, the method of processing a blurred noisy signal has been researched. The conventional method of processing signal has faults which are slow-convergence speed and long time-consuming process at the singular point and in the ill condition. There is the process, the Gauss-Seidel's method to remove these faults, but it takes too much time because it processes signal repeatedly. For overcoming the faults, this paper shows a signal process method which takes shorter than the Tikhnov-Miller's by comparing the Tikhnov-Miller's with proposed algorithm and accelerating convergence speed at the singular point in the ill condition. In this paper, the conventional process method and proposed optimal algorithm were used to get a standard image (256 ＊ 256 ＊ 8bits),and then the results are simulated and compared each other in order to examine the variance of MSE ( Mean-Square Error ) by the acceleration parameter in the proposed two dimensional signal procedures. The result of the signal process and the processing time was measured at all change of acceleration parameter in order to verify the effectiveness of the proposed algorithm.

• Speech Sciences
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• v.9 no.2
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• pp.147-155
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• 2002

In the area of speech processing, raw signals used to be presented into 2D format. However, such kind of presentation methods have limitation to extract characteristics from the signal because of the presentation method. Generally, not much information can be detected from the 2D signal. Strange attractor in the field of chaos theory provides a 3D presentation method. In the area of recognition problem, signal presentation method is very important because good features can be detected from a good presentation. This paper discusses a new feature extraction method that extracts features from a cycle of the strange attractor. A neural network is used to check whether the method extracts suitable features or not. The result shows very good points that can be applied to some areas of signal processing.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.188-193
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• 2010

With GPS being the primary navigation system, Loran use is in steep decline. However, according to the final report of vulnerability assessment of the transportation infrastructure relying on the global positioning system prepared by the John A. Volpe National Transportation Systems Center, there are current attempts to enhance and re-popularize Loran as a GPS backup system through the characteristic of the ground based low frequency navigation system. To advance the Loran system such as Loran-C modernization and eLoran development, research is definitely needed in the field of Loran-C receiver signal processing as well as Loran-C signal design and the technology of a receiver. We have developed a set of Matlab tools, which implement a software Loran-C receiver that performs the receiver's position determination through the following procedure. The procedure consists of receiving the Loran-C signal, cycle selection, calculation of the TDOA and range, and receiver's position determination through the Least Square Method. We experiences the effect of an incorrect cycle selection and various error factors (ECD, ASF, sky wave, CRI, etc.) from the result of the Loran-C signal processing. It is apparent that researches which focus on the elimination and mitigation of various error factors need to be investigated on a software Loran-C receiver. These aspects will be explored in further work through the method such as PLL and Kalman filtering.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.2
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• pp.131-137
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• 2000

In this paper, as a compatible software radio transmission system, Digital-Radio conversion system which can directly change the digital signal generated by the logic circuit into radio signal is proposed. By the vector synthesis method, the digital signals can change directly into radio signal. If such a circuit is realized, RF circuit and an antenna can be composed by the simple one device, and the radio is directly controlled and performed by the software processing which is the essence of software radio. This Digital-Radio conversion system of this paper give many number of communication channels being offered by PN code and offer a hardware design flexibility by digitization, therefore it decrease the percentage ratio of hardware of system and give a more flexible function of software basis. In this paper, the principle of digital to radio signal generation algorithm is explained and the performance characteristics of proposed algorithm is shown in time base by the computer simulation method.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.774-783
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• 2020

For the issue of subsurface target localization by reverse projection, a new approach of target localization with different distances based on symmetric sub-array multiple-input multiple-output (MIMO) radar is proposed in this paper. By utilizing the particularity of structure of the two symmetric sub-arrays, the received signals are jointly reconstructed to eliminate the distance information from the steering vectors. The distance-independent direction of arrival (DOA) estimates are acquired, and the localizations of subsurface targets with different distances are realized by reverse projection. According to the localization mechanism and application characteristics of the proposed algorithm, the grid zooming method based on spatial segmentation is used to optimize the locaiton efficiency. Simulation results demonstrate the effectiveness of the proposed localization method and optimization scheme.