• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.21-31
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• 2020

NCTR(Non-Cooperative Target Recognition) refers to the function of radar to identify target on its own without support from other systems such as ELINT(ELectronic INTelligence). ISAR(Inverse Synthetic Aperture Radar) image is one of the representative methods of NCTR, but it is difficult to automatically classify the target without an identification database due to the significant changes in the image depending on the target's maneuver and location. In this study, we discuss how to build an identification database using simulation and deep-learning technique even when actual images are insufficient. To simulate ISAR images changing with various radar operating environment, A model that generates and learns images through the process named 'Perfect scattering image,' 'Lost scattering image' and 'JEM noise added image' is proposed. And the learning outcomes of this model show that not only simulation images of similar shapes but also actual ISAR images that were first entered can be classified.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.2
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• pp.189-195
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• 2015

There are many research works on the SAR image generation using EM(Electro Magnetic) simulation. Particularly, there are several dedicated S/Ws for SAR image generation and analysis. But, most of them are not available to the public due to the reason for defense and security. In this paper, we describe the generation of ISAR images for a realistic target model using the general purpose EM simulator like FEKO. This method can benefit us many advantages like building the database of many targets for target recognition with cost-and-time effective way.

• Journal of the Korea Society for Simulation
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• v.30 no.4
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• pp.21-29
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• 2021

Inverse synthetic aperture radar (ISAR) image is a powerful tool to show the major scattering regions (scatterer points) on the target. It is normally used to identify and classify targets. Finding information for the scatter points of ISAR image plays an important role in modeling the features of targets. In this paper, we propose a modeling method to extract some information about the scatterer points by minimizing approximating error. Here, the extracted information include not only the location of scatterer points but also some statistical data about the error of the their location. These extracted data can be used to implement the randomness of the location of the scatterer points. Furthermore, we reconstruct an image from the extracted data for scatterer points obtained by our proposed method. And we show that the reconstructed ISAR image is well approximated to the original ISAR image in order to justify our proposed modeling 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.27 no.8
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• pp.758-765
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• 2016

This paper proposes a novel method for the recognition of the inverse synthetic aperture radar(ISAR) image of multiple targets flying in formation. Rather than separating the ISAR image of each target, the proposed method combines an ISAR image obtained by fusing the ISAR images in the training database. Fusion is conducted by optimizing the non-linear problem whose parameters are the aspect angle and the target location. Assuming that the aspect angle is properly estimated, the proposed method estimates the number of the targets and their locations by optimizing the template matching using PSO. In simulations using the F-16 scale model, the efficiency of the proposed method was demonstrated by yielding the ISAR image identical to that of targets in formation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.1
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• pp.69-75
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• 2016

In this paper, we propose a inverse synthetic aperture radar(ISAR) rotational motion compensation(RMC) method to remove residual blurring caused by non-uniform rotational motion of a target. First, a range bin having an isolated scatterer is selected. Next, polynomial phase signal in the selected range bin is estimated by using both Fourier transform(FT) and polynomial-phase transform(PPT). Finally, a new slow time variable that uniformly samples radar signal along the aspect angle directions is defined by using the estimated phase signal, and we interpolate radar signal in terms of the new time variable. As a result, rotational motion to blurr ISAR images is removed, and focused ISAR images are obtained. Simulation results using battleship model validate the robustness and effectiveness of our proposed RMC method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.9
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• pp.740-748
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• 2017

In this paper, we compared performance of conventional inverse synthetic aperture radar(ISAR) imaging methods for maritime target with real data measured by X-band radar. Following conventional approaches were used for performance comparisons: 1) range instantaneous Doppler(RID) method, 2) range Doppler(RD) processing with phase adjustment, and 3) RD processing with prominent point processing(PPP). It is noteworthy that the comparison results have significance of providing basic concept to establish ISAR imaging frame work for maritime targets.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.11
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• pp.1285-1294
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• 2010

This study describes the design and verification of short range UWB(Ultra Wideband) imaging radar that is able to display high resolution radar image for front area of a UGV(Unmanned Ground Vehicle). This radar can help a UGV to navigate autonomously as it detects and avoids obstacles through foliage. We describe the relationship between bandwidth of transmitting signal and range resolution. A vivaldi antenna is designed and it's radiation pattern and reflection are measured. It is easy to make array antenna because of small size and thin shape. Aperture size of receiving array antenna is determined by azimuth resolution of radar image. The relation of interval of receiving antenna array, image resolution and aliasing of target on a radar image is analyzed. A vector network analyzer is used to obtain the reflected signal and corner reflectors as targets are positioned at grass field. Applicability of the proposed radar to UGV is proved by analysis of image resolution and penetrating capability for grass in the experiment.

• 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.

• 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.