• Journal of Communications and Networks
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• v.17 no.5
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• pp.491-498
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• 2015

Recognition of radar emitter signals is one of core elements in radar reconnaissance systems. A novel method based on singular value decomposition (SVD) and the main ridge slice of ambiguity function (AF) is presented for attaining a higher correct recognition rate of radar emitter signals in case of low signal-to-noise ratio. This method calculates the AF of the sorted signal and ascertains the main ridge slice envelope. To improve the recognition performance, SVD is employed to eliminate the influence of noise on the main ridge slice envelope. The rotation angle and symmetric Holder coefficients of the main ridge slice envelope are extracted as the elements of the feature vector. And kernel fuzzy c-means clustering is adopted to analyze the feature vector and classify different types of radar signals. Simulation results indicate that the feature vector extracted by the proposed method has satisfactory aggregation within class, separability between classes, and stability. Compared to existing methods, the proposed feature recognition method can achieve a higher correct recognition rate.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.47-53
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• 2014

We propose a parameter estimation algorithm for radar signal active cancellation based on the Pade approximation that requires much less samples than the conventional MLE scheme. We also verify that the radar signal with time-variant center frequency can be estimated with proposed algorithm by renovating the center frequency. We present simulation results for radar signal active cancellation to show the accuracy of estimated signal using proposed algorithm by calculating the ratio of RMSE of estimated signal to amplitude of hostile radar signal.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.7
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• pp.581-588
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• 2021

This paper deals with a beam scheduling method in fighter interleaving mode. Not only the priority of tasks but also operational requirements that air-to-ground and air-to-air search tasks should be executed alternatively are established to maximize high-quality of situational awareness. We propose a real-time heuristic beam scheduling method that is advanced from WMDD to satisfies the requirements. The proposed scheduling method is implemented in a simulation environment resembling the task processing mechanism and measurement model of a radar. Performance improvement in terms of task delay time is observed.

• ETRI Journal
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• v.43 no.6
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• pp.991-1003
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• 2021

Automatic modulation classification is essential in radar emitter identification. We propose a cascade classifier by combining a support vector machine (SVM) and convolutional neural network (CNN), considering that noise might be taken as radar signals. First, the SVM distinguishes noise signals by the main ridge slice feature of signals. Second, the complex envelope features of the predicted radar signals are extracted and placed into a designed CNN, where a modulation classification task is performed. Simulation results show that the SVM-CNN can effectively distinguish radar signals from noise. The overall probability of successful recognition (PSR) of modulation is 98.52% at 20 dB and 82.27% at -2 dB with low computation costs. Furthermore, we found that the accuracy of intermediate frequency estimation significantly affects the PSR. This study shows the possibility of training a classifier using complex envelope features. What the proposed CNN has learned can be interpreted as an equivalent matched filter consisting of a series of small filters that can provide different responses determined by envelope features.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.413-422
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• 2013

In recent, the rainfall is showing different properties in space and time but the ground rain gauge only can observe rainfall at a point. This means the ground rain gauge has the limitations in spatial and temporal resolutions to measure rainfall and so there is a need to utilize radar rainfall which can consider spatial distribution of rainfall This study tried to apply radar rainfall for runoff simulation on an urban drainage system. The study area is Guro-gu, Seoul and we divided study area into subbasins based on rain gauge network of AWS(Automatic Weather station). Then the radar rainfalls were adjusted using rainfall data of rain gauge stations the areal rainfalls were obtained. The runoffs were simulated by using XP-SWMM model in subbasins of an urban drainage system. As the results, the adjusted radar rainfalls were underestimated in the range of 60 to 95% of rain gauge rainfalls and so the simulated runoffs from the adjusted radar and gauge rainfalls also showed the differences. The runoff peak time from radar rainfall was occurred more fast than that from gauge rainfall.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.307-322
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• 1992

For designing the radar integrated data network, we construct the network structure with a spatial hieratchy decomposition scheme. The RIDN can be decomposed into several subent classes, those of which are composed of the several group classes of radar sites, In a group class. The communication nodes of a radar site are modeled by the software modules formulated with the statistical attributes of discrete events. And we get the analysis over the network through the separately constructed infra group level models which were coded with the C language.From the result of the simulation. We could findthe fact that the data integration system;s performance approaches to the theordtically calculated value after being stable. And also we could get the packet processing status of a communication module’s inner processor which is difficult to oberve through the mathematical calculation tin the subnet model of the integrated data network.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.121-124
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• 2015

In this paper, we developed the compact Doppler radar using the compact dual-circularly polarized antenna for medical application. The operating frequency is 2.47 GHz for considering ISM band. In order to decrease the size of the entire system, we designed the compact antenna and located the circuit board at the back of the antenna. The simulation of the proposed antenna was performed by the finite difference time domain (FDTD) method. The total volume of the proposed system is $65{\times}45{\times}6mm^3$ including the antenna. From the experiment, the developed bio-radar could be used to support the device for medical applications.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.920-929
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• 2005

This paper presents controller design method for nonlinear radar gimbal system with parameter uncertainty and time delay. In order to consider nonlinearity of gimbal bearing frictional torque, we firstly represent fuzzy model for the nonlinear gimbal system, which is achieved by fuzzy combination of linear models through nonlinear fuzzy membership functions. And secondly we propose a delay dependent fuzzy $H_\infty$ controller design method for the delayed fuzzy model with parameter uncertainty and design radar gimbal controller. The designed controller stabilize gimbal system and guarantee $H_\infty$ performance. A computer simulation is given to illustrate stabilized control performances of the designed controller.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.4
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• pp.167-172
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• 2014

In this paper we propose a waveform design algorithm that localizes the maximum output power in the target direction. We extend existing monostatic radar optimal waveform design schemes to bistatic multiple-input multiple-output (MIMO) radar systems. The algorithm simultaneously calculates the direction of departure (DoD) and the direction of arrival (DoA) using a two-dimensional multiple signal classification (MUSIC) method, and successfully localizes the maximum transmitted power to the target locations by exploiting the calculated DoD. The simulation results confirm the performance of the proposed algorithm.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.973-974
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• 2008

As radar signal environments become denser and more complex, the capability of high-speed and accurate signal analysis is required for ES(Electronic warfare Support) system to identify individual radar signals at real-time. In this paper, we propose the new novel clustering algorithm of radar pulses to alleviate the load of signal analysis process and support reliable analysis. The proposed algorithm uses KDE(Kernel Density Estimation) and its CDF(Cumulative Distribution Function) to compose clusters considering the distribution characteristics of pulses. Simulation results show the good performance of the proposed clustering algorithm in clustering and classifying the emitters.