• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.93-100
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• 2018

Inverse Synthetic Aperture Radar(ISAR) image is 2-dimensional radar cross section distributions of a target. For target approaching along radar's line of sight(LOS), the bistatic ISAR can compensate for the weakness of the monostatic ISAR which can not obtain the vertical resolution of the image. However, bistatic ISAR have longer processing times and variability in scattering mechanisms than monostatic ISAR, so target identification using only bistatic ISAR images can be inefficient. Therefore, this paper analyzes target identification performance using monostatic and bistatic ISAR images of targets approaching along radar's LOS and proposes a method of target identification through fusion of two radars. Simulation results demonstrate that identification performance through fusion is more efficient than identification performance using only monostatic, bistatic ISAR images.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.67-76
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• 2022

Monostatic/Bistatic inverse synthetic aperture radar (ISAR) images are two-dimensional radar cross section (RCS) distributions of a target. When there are many targets in a single radar beam, ISAR images are generated with targets overlapped, so it is difficult to perform the targets identification using the trained database. In addition, it is inefficient to perform target identification using only single monostatic and bistatic ISAR images separately because each method has its own advantages and weaknesses. Therefore, this paper analyzes multiple targets identification performances using monostatic/bistatic ISAR images and proposes a method of identification through fusion of two ISAR images. To identify multiple targets, we use image combination technique using trained single target images. Simulation results show effectiveness of proposed method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.12
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• pp.1460-1466
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• 2010

In this paper, we analyzed the performance of radar target classification using the monostatic and bistatic radar cross section(RCS) for four different wire targets. Short time Fourier transform(STFT) and continuous wavelet transform (CWT) were used for feature extraction from the monostatic RCS and the bistatic RCS of each target, and a multi-layered perceptron(MLP) neural network was used as a classifier. Results show that CWT yields better performance than STFT for both the monostatic RCS and the bistatic RCS. And, when STFT was used, the performance of the bistatic RCS was slightly better than that of the monostatic RCS. However, when CWT was used, the performance of the monostatic RCS was slightly better than that of the bistatic RCS. Resultingly, it is proven that bistatic RCS is a good cadndidate for application to radar target classification in combination with a monostatic RCS.

• Journal of electromagnetic engineering and science
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• v.14 no.2
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• pp.79-81
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• 2014

In B-scan data measured by a pulse-type monostatic borehole radar, target signatures are seriously obscured by two clutters that differ in orientation and intensity. The primary clutter appears as a nearly constant time delay, which is caused by internal ringing between antenna and transceiver in the radar system. The secondary clutter occurs as an oblique time delay due to the guided borehole wave along the logging cable of the radar antenna. This issue led us to perform adaptive filtering processing for orientation-based clutter removal. This letter describes adaptive filtering processing consisting of a combination of edge detection, data rotation, and eigenimage filtering. We show that the hyperbolic signatures of a dormant air-filled tunnel target can be more distinctly enhanced by applying the proposed approach to the B-scan data, which are measured in a well-suited test site for underground tunnel detection.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.9
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• pp.693-700
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• 2018

In this paper, we propose a method to generate SAR(synthetic aperture radar) images for bistatic radar. The bistatic SAR can overcome several limitations of monostatic SAR, because the former can be applied to a variety of scenarios, compared to the latter. However, no study has been conducted on bistatic SAR imaging so far. In this paper, we propose a method to generate bistatic SAR images using the monostatic equivalent model and conventional monostatic SAR imaging algorithms. Simulations using airborne SAR in the bistatic geometry validated the efficacy of the proposed method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.9
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• pp.928-935
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• 2013

This paper proposed a combining technique of feature vectors which improves the performance of radar target recognition. The proposed method obtains more information than monostatic or bistatic case by combining extracted feature vectors from two receivers. For verifying the performance of the proposed method, we calculated monostatic and bistatic RCS(BRCS) of three full-scale fighters by changing the receiver position. Then, the scattering centers are extracted using 1-D FFT-based CLEAN from the calculated RCS data. Scattering centers are used as feature vectors for neural network classifier. The results show that our method has the better performance than the monostatic or bistatic case.

• Journal of electromagnetic engineering and science
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• v.18 no.3
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• pp.206-211
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• 2018

In this paper, we proposed a two-level feature vector fusion technique to improve the performance of target classification. The proposed method combines feature vectors of the early-time region and late-time region in the first-level fusion. In the second-level fusion, we combine the monostatic and bistatic features obtained in the first level. The radar cross section (RCS) of the 3D full-scale model is obtained using the electromagnetic analysis tool FEKO, and then, the feature vector of the target is extracted from it. The feature vector based on the waveform structure is used as the feature vector of the early-time region, while the resonance frequency extracted using the evolutionary programming-based CLEAN algorithm is used as the feature vector of the late-time region. The study results show that the two-level fusion method is better than the one-level fusion method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.246-252
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• 2016

In this paper, reduction of monostatic RCS by DBD plasma is measured. For the calibration of monostatic RCS, S-parameters of two metallic plate in different sizes are used and the result is within 0.4 dB error. Metallic plate is put behind DBD plasma generator for measuring reduction of monostatic RCS by DBD plasma. To prevent arc discharge between metallic plate and DBD plasma generator, measurement is progressed spacing the interval between metallic plate and DBD plasma generator. As a result, maximum reduction of monostatic RCS is about 3 dB at 7.4 GHz.

• Journal of electromagnetic engineering and science
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• v.17 no.3
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• pp.153-158
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• 2017

This work reports on the effect of plasma area on the frequency characteristics of the monostatic radar cross section (RCS) of a square metallic plate. A dielectric barrier discharge (DBD) plasma actuator consisting of 10 rings is proposed. The actuator is fabricated in three different configurations such that only three inner rings, seven inner rings, and all rings can be biased. By applying an 18-kV bias at 1 kHz, the three types of DBD actuators generate plasma with a total area of 16.96, 36.74, and $53.69cm^2$, respectively, in a ring or circular form. The experimental results reveal that when the DBD actuator is placed in front of a $20mm{\times}20cm$ conducting plate, the monostatic RCS is reduced by as much as 18.5 dB in the range of 9.41-11.65 GHz. Furthermore, by generating the plasma and changing the area, the frequency of maximum reduction in the monostatic RCS of the plate can be controlled. The frequency is reduced by nearly 20% in the X band when all rings are biased. Finally, an electromagnetic model of the plasma is obtained by comparing the experimental and full-wave simulated results.

• Journal of electromagnetic engineering and science
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• v.12 no.1
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• pp.101-106
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• 2012

In this study, we investigated the effect of groove pattern and gap-fill with lossy materials at 15 GHz frequency of Ku-band. We used Epoxy/MWCNT composite materials as gap-fill materials. Although epoxy does not have an absorbance capability, epoxy added conductive fillers, which are multi-walled carbon nanotubes (MWCNT), can function as radar absorbing material. Specimens were fabricated with different MWCNT mass fractions (0, 0.5, 1.0, 2.0 wt%) and their permittivity in the Ku-band was measured using the waveguide technique. We investigated the effect of gap-fill on monostatic RCS by calculating RCS with and without gap-fill. For arbitrarily chosen thickness and experimentally obtained relative permittivity, we chose the relative permittivity of MWCNT at 2 wt% (${\varepsilon}_r$=8.8-j2.4), which was the lowest reflection coefficient for given thickness of 3.3 mm at V-pol. and $80^{\circ}$ incident angle. We also checked the monostatic RCS and the field intensity inside the groove channel. In the case of H-pol, gap-fill was not affected by the monostatic RCS and magnitude was similar with or without gap-fill. However, in the case of V-pol, gap-fill effectively reduced the monostatic RCS. The field intensity inside the groove channel reveals that different RCS behaviors depend on the wave polarizations.