• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.88-99
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• 2004

A development of a software on radar target signature analysis is presented in this paper The target signature includes Radar Cross Section(RCS) prediction, Range Profile(RP) processing and Inverse Synthetic Aperture Radar(ISAR) processing. Physical Optics(PO) is the basic calculation method for RCS prediction and Geometrical Optics(GO) is used for ray tracing in the field calculation of multiple reflection. For RP and ISAR, Fast Fourier Transform(FFT) and Matrix Pencil(MP) method were implemented for post-processing. Those results are integrated into two separate softwares named as Radar Target Signature Generator(RTSG) and Radar Target Signature Analyser(RTSA). Several test results show good performances in radar signature prediction and analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5103-5115
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• 2015

In radar imaging, a target is usually consisted of a few strong scatterers which are sparsely distributed. In this paper, an improved sparse signal recovery algorithm based on smoothed l₀ (SL0) norm method is proposed to achieve high resolution ISAR imaging with limited pulse numbers. Firstly, one new smoothed function is proposed to approximate the l₀ norm to measure the sparsity. Then a single loop step is used instead of two loop layers in SL0 method which increases the searching density of variable parameter to ensure the recovery accuracy without increasing computation amount, the cost function is undated in every loop for the next loop until the termination is satisfied. Finally, the new set of solution is projected into the feasible set. Simulation results show that the proposed algorithm is superior to the several popular methods both in terms of the reconstruction performance and computation time. Real data ISAR imaging obtained by the proposed algorithm is competitive to several other methods.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.147-157
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• 2018

There are increasing demands to provide early warning against intruding drones and cope with potential threats. Commercial anti-drone systems are mostly based on simple target detection by radar reflections. In real scenario, however, it becomes essential to obtain drone radar signatures so that hostile targets are recognized in advance. We present experimental test results that micro-Doppler radar signature delivers partial information on multi-rotor platforms and exhibits limited performance in drone recognition and classification. Afterward, we attempt to generate high resolution profile of flying drone targets. To this purpose, wide bands radar signals are employed to carry out inverse synthetic aperture radar(ISAR) imaging against moving drones. Following theoretical analysis, experimental field tests are carried out to acquire real target signals. Our preliminary tests demonstrate that high resolution ISAR imaging provides effective measures to detect and classify multiple drone targets in air.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.328-336
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• 2020

This paper presents an asymptotic analysis method using the PO(physical optics) approximation technique to analyze the scattering contribution of an electrically large object partially coated with a radar absorbing material(RAM). By using the feature of the PO technique that can calculate the equivalent current value for each mesh independently, instead of analyzing the entire structure, scattering analysis was performed only by calculating the current on the area where the RAM coating is applied. By the numerical examples, the accuracy and the computation time of the proposed method were verified, and the computational efficiency of inverse synthetic aperture radar(ISAR) of the electrically large objects that require enormous resources is improved.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.12-19
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• 2022

Artificial intelligence is driving the Fourth Industrial Revolution and is in the spotlight as a general-purpose technology. As the data collection from the battlefield increases rapidly, the need to us artificial intelligence is increasing in the military, but it is still in its early stages. In order to identify maritime targets, Republic of Korea navy acquires images by ISAR(Inverse Synthetic Aperture Radar) of maritime patrol aircraft, and humans make out them. The radar image is displayed by synthesizing signals reflected from the target after radiating radar waves. In addition, day/night and all-weather observations are possible. In this study, an artificial intelligence is used to identify maritime targets based on radar images. Data of radar images of 24 maritime targets in Republic of Korea and North Korea acquired by ISAR were pre-processed, and an artificial intelligence algorithm(ResNet-50) was applied. The accuracy of maritime targets identification showed about 99%. Out of the 81 warship types, 75 types took less than 5 seconds, and 6 types took 15 to 163 seconds.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.467-475
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• 2014

In this paper, we introduce a sparse recovery algorithm applied to a radar signal model, based on the compressive sensing(CS), for the formulation of the radar signatures, such as high-resolution range profile(HRRP) and ISAR(Inverse Synthetic Aperture Radar) image. When there exits missing data in observed RCS data samples, we cannot obtain correct high-resolution radar signatures with the traditional IDFT(Inverse Discrete Fourier Transform) method. However, high-resolution radar signatures using the sparse recovery algorithm can be successfully recovered in the presence of data missing and qualities of the recovered radar signatures are nearly comparable to those of radar signatures using a complete RCS data without missing data. Therefore, the results show that the sparse recovery algorithm rather than the DFT method can be suitably applied for the reconstruction of high-resolution radar signatures, although we collect incomplete RCS data due to unwanted interferences or jamming signals.

• Journal of Gastric Cancer
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• v.13 no.2
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• pp.73-78
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• 2013

Surgery is still considered to be the mainstay for the treatment of localized gastric cancer with negative margins (R0-resection) and an adequate lymph-node-dissection (D2-lymphadenectomy). Unfortunately, most cases of gastric cancer are only diagnosed at an advanced stage due to frequent recurrences after primary resection in curative intent. In order to improve prognosis after curative resection, in the recent past, patients with locally advanced tumors were subjected to a pre-, peri-, or postoperative treatment. Interestingly, postoperative chemotherapy has significantly improved survival after gastric resection in Asia, adjuvant radiochemotherapy is favored in North America and perioperative chemotherapy is considered as a treatment of choice in Europe indicating region specific approach towards the treatment. Recently there has also been growing evidence of positive outcomes of neoadjuvant radiochemotherapy on patient survival. In the present article, we discuss the concepts of neoadjuvant treatment approach and provide recommendations to surgeons based on current evidence.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10B
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• pp.1803-1812
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• 2000

A new motion compensation method for ISAR is presented in this paper. It employs amplitude limiting and integration of consecutive range profiles to improve the range and phase alignment accuracy and to alter the propagation properties of compensation errors. These allow the image quality to be significantly improved. It is shown from the imaging results that the new motion compensation algorithm can get images of targets in field situations with much better quality than the traditional cross-correlation algorithm.

• The Magazine of the IEIE
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• v.43 no.10
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• pp.49-54
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• 2016

• River and Culture
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• v.6 no.3
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• pp.93-103
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• 2010