• 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

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.7
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• pp.730-736
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• 2013

Time-domain clutter generation model for airborne pulse doppler phase-array radar is presented. Time-domain surface clutter signal is generated assuming earth of a sphere and considering geometry of a clutter patch, and generation of sub-array clutter signal is presented. The generated sub-array clutter signal can be used by simulation input signal in various radar applications of DBF(Digital Beamforming), ABF(Adaptive Beamforming), Stap(Space-Time Adaptive Processing) and etc.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.11
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• pp.1204-1212
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• 2008

The paper proposes a new signal model which is revised from the commonly used signal model. Recently, many research institutions had a research about CW bio-radar for detecting he heartbeat and respiration. However, when the bio-radar detects the heartbeat using the previous signal model, the bio-radar has a disadvantage of weakness about he residual phase and AWGN. Also, the model is inappropriate in ergonomics because this signal model supposes hat the heart and lung are located at a same place. In this paper, the modified signal model, which is appropriate n ergonomics, is proposed. This paper analyzes and compares with the performance for detecting the heartbeat and respiration using the previous model and revised model in AWGN and multi-path environment.

• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.75-78
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• 2005

The detectability of radar depends on RCS(radar cross section). The RCS for complex radar targets may be only approximately calculated by using low-frequency or high-frequency scattering methods, while the RCS for simple radar targets can be exactly obtained by applying on eigen-function method. However, the conventional methods for calculation of RCS are computationally complex. We propose an radar signal model for RCS calculation by MUSIC algorithm In this research, it is assumed that the radar target is considered as a ring of scatterers. The amplitudes of scatterers may be statistically distributed. As the result, the radar signal model is proposed to use MUSIC, and the RCS is calculated by a simple linear algebraic method.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1279-1284
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• 2000

This study introduces a simulation model of radar responses with frequencies on subsurface voids in concrete. In this model, the resolution and the attenuation according to radar frequencies in each interface which has different electromagnetic property are analyzed. This model aims to select the best frequency of radar which can analyze the thickness of voids in concrete from radar response. It also can be applied to estimate the limitation of propagation depth of radar on subsurface voids in concrete. The computed results show the radar images based on radar signal processing using convolution technique.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.536-546
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• 2003

We propose an object extraction technique adequate for the radial shape's radar signal structure for the purpose of implementing ARPA(Automatic Radar Plotting Aid) installed in the vessel. The radar signal data are processed by interpolation and accumulation to acquire a qualified image. The objects of the radar image have characteristics of having different shape and size as it gets far from the center, and it is not adequate for clustering generally. Therefore, this study designs a new vigilance distance model of elliptical shape and adopts this model in the ART2 neural network. We prove that the proposed clustering method makes it possible to extract objects adaptively and to separate the connected objects effectively.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.4
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• pp.80-88
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• 2003

Radar signal simulation is increasingly gaining in importance according as modem radar systems are more complex. Although computer performance has been advanced, it is difficult to implement the real-time simulation because the detailed model for the radar is necessary to get the desired accuracy. In order to achieve real time operation, we propose radar signal generation technique using ambiguity function, Instead of wellknown correlation method. The ambiguity function is the mathematical modeling of the signal processing procedure which is a simulation section to require the most computations.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.3
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• pp.246-251
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• 2023

RADAR(Radio Detection and Ranging) is an important system for surveillance and reconnaissance by detecting a reflected signal which obtains the range from the radar to the target, and the velocity of the target. The magnitude of the reflected signal varies due to the radar cross section of the target, characteristic of the transmission and reception antenna, distance between the radar and the target, and power and wavelength of the transmitted signal. Thus, the RCS is the important characteristic of the target to determine if the target can be observed by the RADAR system. It is based on the material and shape of the target. We have measured the reflection signal of a simple square-shaped (20 × 20 cm) target made of a new material, a gallium-based liquid metal alloy and compared that of well-known metals including copper, aluminum. The magnitude of reflected signal of the aluminum target was the largest and it was 2.4 times larger than that of the liquid metal target. We also investigated the effect of the shape by measuring reflectance of the F-22 3D model(~1/95 ratio) target covered with/without copper, aluminium, and liquid metal. The largest magnitude of the reflected signal measured from side-view with the copper-covered F-22 model was 2.6 times greater than that of liquid metal. The reflectance study of the liquid metal would be helpful for liquid metal-based frequency selective surface or metamaterials.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.652-659
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• 2009

To analyze and verify the performance of a pulse radar without the real target data, there is a need to make the simulated signal which is similar to the received signal of the real target. In this paper, a method of the received signal generation for the pulse radar is proposed to solve the above need. The user-made scenarios are used to model the fast and small target and the clutter data based on the ground environment. These data are transformed into the electric signal using the proposed method. The efficiency of the proposed method is proved by comparing the signal of a field test with the simulated signal.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.2
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• pp.170-178
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• 2019

Classification of radar signals in the field of electronic warfare is a problem of discriminating threat types by analyzing enemy threat radar signals such as aircraft, radar, and missile received through electronic warfare equipment. Recent radar systems have adopted a variety of modulation schemes that are different from those used in conventional systems, and are often difficult to analyze using existing algorithms. Also, it is necessary to design a robust algorithm for the signal received in the real environment due to the environmental influence and the measurement error due to the characteristics of the hardware. In this paper, we propose a radar signal classification method which are not affected by radar signal modulation methods and noise generation by using deep learning techniques.