• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.9
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• pp.906-913
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• 2004

FFT algorithm is the most popular ISAR imaging technique from radar data. It requires polar formatting technique to make a focused image of the target as MTRC(Moving Through Resolution Cell) causes a blurred image when the data is from the wide azimuth angle. But there exits the angle limit for the application of the polar formatting and we cannot obtain clear images if the range of the azimuth angle is too wide to process with polar, formatting. This paper analyses the relative merits of the polar formatting algorithm accompanied by interpolation to the CDT algorithm that needs not the interpolation.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.158-163
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• 2008

In inverse synthetic aperture radar (ISAR) imaging, An ISAR autofocusing algorithm is essential to obtain well-focused ISAR images. Traditional methods have relied on the approximation that the phase error due to target motion is a function of the cross-range dimension only. However, in the stepped-frequency radar system, it tends to become a two-dimensional function of both down-range and cross-range, especially when target's movement is very fast and the pulse repetition frequency (PRF) is low. In order to remove the phase error along down-range, this paper proposes a method called SAEM (subarray averaging and entropy minimization) [1] that uses a subarray averaging concept in conjunction with the entropy cost function in order to find target motion parameters, and a novel 2-D optimization technique with the inherent properties of the proposed entropy-based cost function. A well-focused ISAR image can be obtained from the combination of the proposed method and a traditional autofocus algorithm that removes the phase error along the cross-range dimension. The effectiveness of this method is illustrated and analyzed with simulated targets comprised of point scatters.

• 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.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.5
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• pp.680-687
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• 2014

PGA(phase gradient autofocus) has been widely used to remove motion induced phase errors in the ISAR(inverse synthetic aperture radar) imaging. The critical process for the processing time and image quality is windowing stage in PGA. In this paper, the new method to determine window size based on polynomial least square approximation is proposed. Moreover, dominant range bins are selected for efficient phase error estimation, which improve image quality and speed up convergence. The simulation results show that the proposed algorithm provides high quality ISAR images while computational efficiency of inherent PGA is retained.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.4
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• pp.397-403
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• 2015

In this paper, a method of ISAR geometric calibration is represented by using impulse-radio UWB radar. The ir-UWB is good for using a signal processing in time domain, so, it does not occur a multi-path or coupling problem. If a signal that between antennas and target is assumed a plane wave, a center of rotation in ISAR geometry model can be estimated by using point target. Before image is reconstructed with sinogram, the center of rotation can be calculated by using least square fitting. This method can be obtained a more contrast image, and a maximum value of entropy of image. The method, that estimates a center of rotation in received data, will be used a initial setup of instruments or a periodic compensation to reconstruct image. It would be useful in medical, security and surveillance imaging equipments that have a fixed geometry.