• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.7
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• pp.717-722
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• 2007

Inverse synthetic aperture radar(ISAR) images represent two-dimensional(2-D) spatial distribution of electromagnetic scattering phenomenology against a target. Hence, they are usually used in the areas of automatic target recognition (ATR) or non-cooperative target recognition(NCTR), identifying a target using radar in a long distance. This paper makes use of Korea Miniature Synthetic Aperture Radar(KOMSAR) to generate ISAR images of a real and maneuvering aircraft. The data obtained from KOMSAR are processed to eliminate phase errors due to motion of a target, with the use of entropy-based ISAR autofocusing technique. Results show that we can successfully obtain ISAR images of a real aircraft, and the success of experiments implies that a significant step toward ATR using radar has been established.

• 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.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.25 no.9
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• pp.930-937
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• 2014

Inverse synthetic aperture radar (ISAR) images can be generated by radar which radiates the electromagnetic wave to a target and receives signal reflected from the target. ISAR images can be widely used to target detection and recognition. This paper proposed a method of generation of high resolution ISAR images by synthesizing frequency spectrums of each stepped chirp waveform in one burst and sub-sampling in frequency domain. This process is performed over entire bursts during coherent processing interval. Conventional ISAR image generation method using stepped frequency waveform has a severe problem of short unambiguous range, loading to ghost phenomenon. However, this problem can be resolved by the proposed method. In simulations, we generate high resolution ISAR image of the moving target which is Boeing-737 aircraft model composed of several ideal point scatterers.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.3
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• pp.294-303
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• 2008

ISAR(Inverse Synthetic Aperture Radar) images represent the 2-D(two-dimensional) spatial distribution of RCS (Radar Cross Section) of an object, and they can be applied to the problem of target identification. A traditional approach to ISAR imaging is to use a 2-D IFFT(Inverse Fast Fourier Transform). However, the 2-D IFFT results in low resolution ISAR images especially when the measured frequency bandwidth and angular region are limited. In order to improve the resolution capability of the Fourier transform, various high-resolution spectral estimation approaches have been applied to obtain ISAR images, such as AR(Auto Regressive), MUSIC(Multiple Signal Classification) or Modified MUSIC algorithms. In this study, these high-resolution spectral estimators as well as 2-D IFFT approach are combined with a recently developed ISAR image classification algorithm, and their performances are carefully analyzed and compared in the framework of radar target recognition.

• 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.12 no.2
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• pp.299-307
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• 2001

This paper presents a experimental study of Inverse Synthetic Aperture Radar(ISAR) imaging using Matrix Pencil(MP) method. A series of measurement for two types of target model was done in a Compact Range(CR)facility. The first target is a set of distributed slim cylinders to get a ISAR image of point-like scatterers. The second is UAV model representing a complex real target. The results show that ISAR images by MP method are better than by conventional FFT method under the realistic measurement conditions.

• 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.29 no.2
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• pp.109-117
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• 2018

In order to form focused inverse synthetic aperture radar(ISAR) images of a non-uniformly rotating target, rotational motion compensation(RMC) should be performed. Prominent point processing(PPP), one of the most representative RMC methods, is used to compensate nonlinear rotation motion by exploiting the phase signals of scatterers. In this paper, we propose a new RMC method based on the integrated cubic phase function(ICPF). The ICPF requires only one-dimensional(1-D) maximization to estimate the phases of multi-component signals. Simulation results using a point scatterers model in the absence of dominant scatterers validate that PPP based on ICPF can achieve well-focused ISAR images in real time.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.10
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• pp.1062-1068
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• 2014

In this paper, a novel approach estimating target's rotation velocity(RV) is proposed for inverse synthetic aperture radar(ISAR) cross-range scaling(CRS). Scale invariant feature transform(SIFT) is applied to two sequently generated ISAR images for extracting non-fluctuating scatterers. Considering the fact that the distance between target's rotation center(RC) and SIFT features is same, we can set a criterion for estimating RV. Then, the criterion is optimized through the proposed method based on particle swarm optimization(PSO) combined with exhaustive search method. Simulation results show that the proposed algorithm can precisely estimate RV of a scenario based maneuvering target without RC information. With the use of the estimated RV, ISAR image can be correctly re-scaled along the cross-range direction.