• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1753-1759
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• 2009

A weather radar as one of the remote sensing devices to analyze the weather phenomena receives the return echoes which consist of scattered electromagnetic wave signals from rain, cloud and dust particles, etc. These received Doppler weather spectra are analyzed to extract the various characteristic weather information. The mean wind velocity is one of the important weather parameters which can be obtained by a weather radar ed it may be useful in the prevention of weather hazards occurred by the abrupt shift of wind in small geographical scales such as microbursts. It is usually estimated by pulse pair method which is considered to be reliable and very efficient in the computational requirement. However, there are some problems in the accurate estimation of the mean velocity if Doppler spectra of weather signals appear to be asymmetric gaussian or multi-peak spectra. Therefore, in this paper, the problems in the mean estimation of asymmetric Doppler spectra are analyzed and the improved method is suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.561-564
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• 2007

Recently, The detection of weather conditions and weather related hazards with a weather radar are being actively investigated based on the echo intensity and the Doppler spectrum analysis. For this purpose, many types of simulated weather signals are needed for investigation. Therefore, this paper analyzed the method to simulate the many weather radar signals.

• Journal of IKEEE
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• v.22 no.3
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• pp.624-629
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• 2018

Classification of moving targets in Pulse Doppler Radar(PDR) for surveillance and reconnaissance purposes is generally carried out based on listening and training experience of Doppler audio signals by radar operator. In this paper, we proposed the automatic classification method to identify the class of moving target with Doppler audio signals using the Mel Frequency Cepstral Coefficients(MFCC) and the Hidden Markov Model(HMM) algorithm which are widely used in speech recognition and the classification performance was analyzed and verified by simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1780-1786
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• 2005

The phase error generated in the transmission system affects the performance of digital transmission signal. The phase error are generated by random phase noise and tracking phase error due to denier phenomenon. In the mobile satellite communication system that generates the doppler frequency, which is a system with a movement, the proper system phase noise spectrum should be designed based on analyses for phase noise and static phase error effects. Based on the analyses of the doppler frequency and the phase error for bilateral satellite communication system providing an asynchronous service, the phase noise spectrums for the mobile satellite communication are designed in this paper. Also, the available transmission services under the less doppler effect are proposed and the proper signal source units for a required transmission system can be designed under the proposed system phase noise spectrum.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.243-249
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• 2019

In this paper, we have developed a device to reduce the standby power consumption that is unnecessarily consumed in unused electrical appliances. The Doppler sensor is used to automatically power off and power off the outlet depending on whether or not a person is present near the outlet. The Doppler sensor uses a coaxial cable trap to design a transmitting antenna and emits a 10 GHz band RF signal and receives a reflected wave signal whose wavelength is reflected from the target object to the receiver to detect an object and recognize human approach. It automatically cuts off and restores standby power to prevent unnecessary power consumption, saving energy and developing a standby power automatic shutdown and recovery device that can prevent the risk of large fires caused by leakage current.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.114-125
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• 2014

In a conventional sonar system, which uses LFM signal for detecting targets with varying speed, the results of multiple LFM Doppler correlators are aligned and the maximum alined result are selected as a test cell for detecting targets. As the number of the LFM Doppler correlators are increased for accurate target detection, as the required computational complexity and the memory are also increased. This fact makes it difficult to implement the accurate LFM target detector. In this paper, we propose a new fast target detection which is robust for the variation of target speed. Because the proposed method uses the summation of alined results of large numbers of LFM Doppler correlators, the proposed method increase SNR and provide robust SNR for the variation of target speed. And the proposed method can provide very fast target detection by implementing the process, the summation of alined results of large numbers of LFM Doppler correlators, as one summation filter.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.534-542
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• 2019

In active SONAR, several different methods are used to detect range-Doppler information of the target. Compressive sensing based method is more accurate than conventional methods and shows superior performance. There are several compressive sensing algorithms for range-Doppler estimation of active sonar. The ability of each algorithm depends on algorithm type, mutual coherence of sensing matrix, and signal to noise ratio. In this paper, we compared and analyzed computational performance and accuracy of various compressive sensing algorithms for range-Doppler estimation of active sonar. The performance of OMP (Orthogonal Matching Pursuit), CoSaMP (Compressive Sampling Matching Pursuit), BPDN (CVX) (Basis Pursuit Denoising), LARS (Least Angle Regression) algorithms is respectively estimated for varying SNR (Signal to Noise Ratio), and mutual coherence. The optimal compressive sensing algorithm is presented according to the situation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2261-2266
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• 2011

Being the most widely used in ultrasound Doppler color flow mapping, the Kasai algorithm, also known as lag-1 autocorrelation method, is capable of estimating the Doppler mean frequency relatively accurately with a modest amount of computation. Particularly in the case of imaging deep lying areas, however, its performance suffers due to low signal-to-noise ratios. The purpose of this paper is to propose a dealiased lag-2 autocorrelation method which is superior to the Kasai algorithm even at low signal-to-noise ratios and to compare their performances through simulations. The proposed algorithm is found to be better by about 2 to 3 dB than the Kasai algorithm in terms of Doppler mean frequency estimation error in the presence of measurement noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.628-631
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• 2008

For the remote sensing purpose, radar systems extract the target information, such as the magnitude of reflectivity and the velocity from the spectrum analysis of return echoes through the Doppler filter bank. This conventional spectrum estimation method, FFT(Fast fourier Transform) is widely used in most radar systems. However, the frequency resolution of return echoes can be seriously degraded in fast moving targets because of the short acquisition time. Since the high Doppler frequency resolution is important in the detection and tracking of fast moving targets, it can cause very unsatisfactory results. Therefore, in this paper, the parameter spectrum estimation method called AR(Autoregressive) spectrum estimation, is investigated to overcome these problems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1777-1783
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• 2013

We do research on the simulation of Doppler effect from a target's moving under the sea by Transmission Line Matrix modeling which is one of numerical methods on time domain. To implement the effect, the input signal was entered at a moving node according to a moving target's moving speed. The result had maximum 2.47% error compared with the theoretical value. And from simulation results with speed control of a moving target, we could also obtain resonable results within 0.63% error range.