• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.85-94
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• 2019

Warhead and debris show the different micro-Doppler frequency shape in the spectrogram because of the different micro motion. So we can classify them using the micro-Doppler features. In this paper, we classified warhead and debris in the separation phase using CNN(Convolutional Neural Networks). For the input image of CNN, we used micro-Doppler spectrogram. In addition, to improve classification performance of warhead and debris, we applied the preprocessing using CA-CFAR to the micro-Doppler spectrogram. As a result, when the preprocessing of micro-Doppler spectrogram was used, classification performance is improved in all signal-to-noise ratio(SNR).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.11
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• pp.61-69
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• 2006

Position determination accuracy is strongly depending on how much precisely and frequently satellite receiver measures transmitted signals from terminals on target animals when Doppler effect is applied for position determination. ARGOS satellite system has shown relatively high position determination accuracy by operating multiple satellites, which enable operator to get more Doppler shift data from terminals. In case of animal tracking mission with single satellite, however, it is difficult for the satellite receiver to receive transmitted signals from terminals frequently during short period that satellite passes over ground terminals. This is one of the main sources to decrease position accuracy on target animals. In this paper, the Doppler rate estimation is implemented to increase the number of Doppler shift data received by single satellite. It is proved that the relatively high position determination accuracy with increased number of estimated data can be obtained. We also suggest that the Doppler rate estimation is applicable for position determination system with single satellite.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1275-1283
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• 2014

Characteristics of PCM(Pulse Code Modulation) waveform are suitable for target tracking. Especially in terms of dwell time, it is desirable to detect and track a moving target with the single PCM waveform for a MFR(Multi-Function Radar) which carries out multiple tasks. General PCM waveform processing includes Doppler filter bank caused by the characteristics of ambiguity function, to detect target and estimate Doppler frequency, which induces hardware burden and computational complexity. We propose a ML(Maximum Likelihood) based Doppler estimator for a PCM waveform, which is the closed form suboptimal solution and computationally efficient to estimate Doppler frequency and detect a moving target.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.461-465
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• 2007

MANET(Mobile Ad hoc Networks) is free-mobility formation of mobile nodes in the wireless networks. Generally, wireless networks has two main type of structures which Tree and Mesh. These general structure is difficult to do which connectivity, redundancy transmit and network continuant. In this paper, we would suggest a new ODDMRP(Ontology Doppler effect-based Dynamic Multicast Routing Protocol) technology for effective MANET which Ontology Doppler effect-based. ODDMRP consist of the parameters for node entropy when using Doppler effect which moving position of round node, moving time, and distribution chart in velocity also it express distance of destination node and property structure organization. It would be used to provide improvement to keep the optimal communication routing and also could be improve network stabilization, and continuation durability of connectivity.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.1
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• pp.33-41
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• 2017

This paper suggests a hand gesture recognition technology to control smart devices using multiple Doppler radars and a support vector machine(SVM), which is one of the machine learning algorithms. Whereas single Doppler radar can recognize only simple hand gestures, multiple Doppler radar can recognize various and complex hand gestures by using various Doppler patterns as a function of time and each device. In addition, machine learning technology can enhance recognition accuracy. In order to determine the feasibility of the suggested technology, we implemented a test-bed using two Doppler radars, NI DAQ USB-6008, and MATLAB. Using this test-bed, we can successfully classify four hand gestures, which are Push, Pull, Right Slide, and Left Slide. Applying SVM machine learning algorithm, it was confirmed the high accuracy of the hand gesture recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.866-869
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• 2015

In this paper, we propose a device for detect front object using low-price the CW Doppler sensor to prevent safety accident such as a bicycle, an electric wheelchair users. For this propose, we develop a signal process board and the object motion detect algorithm using to analyzing output signal of the CW Doppler sensor. Output signal from CW Doppler sensor is analog I and analog Q. The CW Doppler sensor shows phase I and phase Q of object differently when the object approach, stop, drop by sensor. We develop an algorithm that can detect object by discrimination information of phase using the CW Doppler sensor. The verification use firmware of applied hardware and algorithm. Then, the motion information can be confirming output depending on motion object by experiment normally. As a result, we check that the sensing information output by following motion of object and confirm an algorithm and motion of signal processing board.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.310-318
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• 2016

This study deals with a method to localize a noise source occuring in a marine vehicle in a 3D environment. Even when access to the noise source is limited for a marine vehicle, such as a ship or a submarine in operation, the signal received on a hydrophone located elsewhere contains Doppler effected noise by moving relatively. This study suggests noise localization algorithm in 3D based on Doppler effect by moving marine vehicle. Using a known source mounted on the vehicle, the noise source was estimated by reducing the range of Doppler center and closest point of approach via the least square method. The algorithm was verified through various simulations and it was shown that the noise could be localized in 3D based on Doppler effect by employing two fixed hydrophones located at the vehicle's exterior points and a known reference signal generator located somewhere on the vehicle.

• Journal of the Korean Society for Marine Environment & Energy
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• v.18 no.2
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• pp.116-122
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• 2015

A simulation is applied to evaluate sea surface observations such as wave heights and surface currents by using a microwave Doppler radar. It is reported that the microwave irradiation width on the sea surface and Fourier transform time taken to sample data for frequency analysis affect Doppler spectra. To investigate the influences by these parameters, Doppler spectra are simulated with various numerical sea surface waves with currents. From the results, in the case of the microwave irradiation width is five times smaller than the wavelength of the sea surface wave, and the Fourier transform time is also five times shorter than the period of the sea surface wave, there is a possibility to measure wave heights accurately with a Doppler radar. In addition, relative surface currents can be estimated by analysis of long Fourier transform time. The simulation results showed the appropriate observing conditions with a microwave Doppler radar.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.446-454
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• 2002

This paper presents the Doppler Scanning technique which enables us to detect the relative positions of moving distributed sources using Doppler frequency shift estimate when the moving source consists of distributed sources with different signature frequencies. Doppler frequency shifts of characteristic frequencies of machinery noise sources such as ship's generator and propeller, with tine along CPA (Closest Point of Approach of moving source) are unique, and can be functioned with respect to each source position. Therefore, this technique can be applied to estimate the relative geometrical positions between machinery noise sources. The Extended Kalman Filter (EKF) which has a high frequency resolution with high time resolution, is adopted for improving accuracy of Doppler frequency shift estimate geometric resolution of machinery positions since machinery noise sources show in general low frequency band characteristics with limited spacial distance. The performance of the technique is examined by the numerical simulations and is verified by the experiment using loudspeaker sources on the roof of the car.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.1
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• pp.22-34
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• 1997

In LEO system, the signal degradation is mainly due to fading and Doppler shift, so that the analysis of the signal degradation and compensation techniques are very important. As the Doppler shift compensator, the block demodulator has been known to be useful in compensating for the time-varing Doppler shift, but its compensating ability is about several hundreds Hz in 32 ksymbols / s QAM (QPSK) signal transmission. Therefore, in this paper, to compensate for severe fading and Doppler shift more than several kHz, we use a conventional pilot symbol-aided fading compensator, and propose the Doppler shift compensator. It is shown that the proposed compensator is able to compensate for Doppler shift more than several kHz. And a pilot symbol-aided fading compensator is shown to be a suitable scheme for severe Rician fading ($K{\leq}10 dB$) as well as Rayleigh fading. Also, it is shown that the equal gain combiner improves greatly the QAM performance even if the fading or Doppler shift becomes deeper or larger.