• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.10 s.113
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• pp.913-919
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• 2006

This paper presents a technique for motion compensation of ISAR(Inverse SAR) images for a moving target. If a simple fourier transform is employed to obtain ISAR image for a moving target, the image is usually blurred. These images blurring problem can be solved with the time-frequency transform. In this paper, motion compensation algorithms of ISAR image such as STFT(Short Time Fourier Transform), GWT(Gabor Wavelet Transform) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and simulated MIG-25 to obtain motion compensated ISAR image, and display the resolution of STFT and GWT ISAR image.

• 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.18 no.8
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• pp.984-996
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• 2007

This paper presents techniques of 2-D scattering center extraction and 2-B ISAR(Inverse SAR) image formation for scattering wave which is scattered by a target. In general, 2-D IFFT is widely used to obtain 2-D scattering center and ISAR image of targets. But, this method has drawbacks, that is poor in a resolution aspect. To overcome these shortcomings with the FT(Fourier Transform)-based method, various techniques of high resolution signal processing were developed. In this paper, algorithms of 2-D scattering center extraction and ISAR image formation such as 2-D MEMP(Matrix Enhancement and Matrix Pencil), 2-D ESPRIT(Estimation of Signal Parameter via Rotational Invariance Techniques) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and F-18 aircraft to estimate 2-D scattering center and abtain 2-D ISAR image.

• 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.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.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.

• 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 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.11
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• pp.1156-1160
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• 2003

Many time-frequency analysis techniques have been used for motion compensated ISAR(Inverse Synthetic Aperture Radar) imaging. In this work, a novel time-frequency(T-F) analysis called evolutionary adaptive wavelet transform (EAWT) and evolutionary adaptive joint time-frequency(EAJTF) procedure are used for the motion compensated ISAR image. To show the validity of our algorism, we use simulated MIG-25 and Boeing 727(B-727) ISAR data. From the constructed ISAR image using EAWT and EAJTF, we show that our algorithm can obtain a clear motion compensated ISAR image such as other time-frequency analysis techniques.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.1
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• pp.14-19
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• 2010

In this paper, an efficient algorithm is developed to perform target rotational motion compensation to achieve the clear inverse synthetic aperture radar(ISAR) image. The algorithm is based on a time-frequency technique. This algorithm provides an efficient method to resolve the blurring image caused by the time-varying behavior of the target scattering centers and leads to a well-focused ISAR image. Results demonstrate that the time-frequency techniques can improve the blurring ISAR image when an aircraft is in complex motion, such as maneuvering, rotation and acceleration.