• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.451-458
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• 2014

This paper introduces a bistatic ISAR imaging technique. In bistatic geometry, the transmitter and receiver are placed in different locations. The monostatic ISAR is inadequate not only for obtaining images on targets approaching along the radar's line of sight, but also for stealth targets. In this paper, geometry, signal modeling as well as bistatic Doppler for bistatic ISAR are introduced to address these problems. Simulations results show bistatic ISAR images as well as monostatic ISAR images against target's moving scenarios, and analyze their differences for each scenario.

• 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.26 no.6
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• pp.564-571
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• 2015

In this paper, we propose a multiple-input, multiple-output(MIMO) interferometric radar network system to generate three-dimensional (3-D) MIMO interferometric inverse synthetic aperture radar(InISAR) image. In the MIMO interferometric radar network system, the MIMO InISAR image can be formed by an incoherent summation of multiple bistatic InISAR images that show 3-D scatterers of a target observed at different bistatic interfermetric configurations, respectively. Because bistatic-sccattering physics of a target at different viewpoints are visible in the 3-D MIMO InISAR image, it can provide various scatterering physics properties of a target, and can be used for target classification as a useful feature vector. Simulations validate that our proposed method successfully finds locations of scatterers of a target in MIMO radar interferometric network system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.7
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• pp.656-665
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• 2015

In this paper, we improved the clarity and quality of the radar imaging by applying motion compensation for time-frequency transform in B-ISAR imaging. The proposed motion compensation algorithm using UWB radar is verified. B-ISAR algorithm procedure and time-frequency transform for improved motion compensation are provided for theoretical ground. The image was created by a UWB Radar B-ISAR imaging algorithm method. Also, creating a B-ISAR imaging algorithm for motion compensation of time-frequency transformation method was used. The B-ISAR Imaging algorithm is implemented using STFT(Short-Time Fourier Transform), GWT(Gabor Wavelet Transform), and WVD(Wigner-Ville Distribution) approaches. The performance of STFT is compared with the GWT and WVD algorithms. It is found that the WVD image shows more clarity and decreased spread phenomenon than other methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.6
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• pp.566-576
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• 2016

Inverse synthetic aperture radar(ISAR) image generated from bistatic radar(Bi-ISAR) represents two-dimensional scattering distribution of a target, and the Bi-ISAR can be used for bistatic target identification. However, Bi-ISAR has large variability in scattering mechanisms depending on bistatic configurations and do not represent exact range-Doppler information of a target due to inherent distortion. Thus, an efficient training DB construction is the most important factor in target identification using Bi-ISARs. Recently, a database construction method based on realistic flight scenarios of a target, which provides a reliable identification performance for the monostatic target identification, was applied to target identification using high resolution range profiles(HRRPs) generated from bistatic radar(Bi-HRRPs), to construct efficient training DB under bistatic configurations. Consequently, high identification performance was achieved using only small amount of training Bi-HRRPs, when the target is a considerable distance away from the bistatic radar. Thus, flight scenarios based training DB construction is applied to target identification using Bi-ISARs. Then, the capability and efficiency of the method is analyzed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.670-677
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• 2017

In this paper, we propose a rotational motion compensation(RMC) for bistatic inverse synthetic aperture radar(Bi-ISAR) imaging. For this purpose, geometry-error, caused by changes of bistatic-angle, is removed using known position information of a transmitter, a receiver, and target trajectories. Next, RMC is performed to compensate non-uniform rotational motion error by reformatting radar signal in terms of a newly defined slow time variable that converts non-uniform rotational motion into uniform one. Simulation results using an aircraft model composed of ideal point scatterers validate the efficacy of the proposed Bi-ISAR RMC method.