• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.85-94
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• 2019

Warhead and debris show the different micro-Doppler frequency shape in the spectrogram because of the different micro motion. So we can classify them using the micro-Doppler features. In this paper, we classified warhead and debris in the separation phase using CNN(Convolutional Neural Networks). For the input image of CNN, we used micro-Doppler spectrogram. In addition, to improve classification performance of warhead and debris, we applied the preprocessing using CA-CFAR to the micro-Doppler spectrogram. As a result, when the preprocessing of micro-Doppler spectrogram was used, classification performance is improved in all signal-to-noise ratio(SNR).

• International Journal of Aeronautical and Space Sciences
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• v.17 no.4
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• pp.614-621
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• 2016

Micro-Doppler (MD) shift caused by the micro-motion of a ballistic missile (BM) can be very useful to identify it. In this paper, the MD signatures of three scale-model BMs are investigated using a portable measurement system. The measurement system consists of an X-band 2-by-2 phase comparison mono-pulse radar, and a mechanical device that can impart controlled spinning and coning motions simultaneously to a model to yield the MD signature that replicates the characteristic of each target and the corresponding micro-motion. The coning motion determined the overall period of MD, and the spinning motion increased its amplitude. MD was also dependent on aspect angle. The designed system is portable, and can implement many micro-motions; it will contribute to analysis of MD in various situations.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.9
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• pp.1100-1106
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• 2012

This paper has presented the analysis of the micro-Doppler signatures scattered from the blades of the rotating propeller using the modified HHT method, one of the joint time-frequency analysis methods. The field scattered from the blade edge of the propeller was calculated using equivalent current method(ECM). After the acquisition of the scattered field data in the time domain, the modified HHT method was applied to analyze the micro-Doppler signature. The analysis results showed not only a good agreement with the realistic dynamic characteristic of the blade but also sinusoidally varing characteristics of the micro-Doppler signatures generated from rotating objects. It could be concluded that the joint time-frequency analysis via the modified HHT provided the discriminative characteristics for recognizing a small aircraft target with small RCS value.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.139-148
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• 2022

In this paper, we implement a distributed FMCW MIMO radar system to obtain Micro Doppler signatures of target motions. In addition, we also develop federated learning based motion recognition algorithm based on the Micro-Doppler radar signature collected by the implemented FMCW MIMO radar system. Through the experiment, we have verified that the proposed federated learning based algorithm can improve the motion recognition accuracy up to 90%.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.1
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• pp.129-137
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• 2017

When the micro-Doppler (MD) image of a ballistic missile is derived, the translational motion compensation (TMC) method is usually applied to the inverse synthetic aperture radar (ISAR) image, but yields poor results because of the micro-motion of the ballistic missile. This paper proposes an efficient TMC method to obtain a focused MD image of a ballistic missile engaged in complicated micro-motion. During range alignment, range profiles (RPs) are coarsely aligned by using the 1D entropy cost function of RPs as a mark, then the coarsely-aligned RPs are fine-aligned by using the minimum 2D entropy of the MD image. During phase adjustment, the gradient of the phase error is appropriately weighted and added to the previous phase error to further fine-tune the aligned RPs. In simulations using the point scatterer model and the measured data from the real missile model, the proposed method provided better image focus than the existing method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.11
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• pp.996-1003
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• 2016

Trilateration technique using time of arrival(TOA) is generally used for single target position estimation in radar system. However, trilateration technique has limitation in case of multiple targets, since it is difficult to distinguish the measurements corresponding to the respective targets. In this study, to eliminate ambiguity of relation between measurements and targets, micromotion of each target is measured by micro Doppler which is actively studied in radar industry nowadays and these information are used to distinguish measurements used at trilateration technique. Resultingly, the trilateration technique is applied successfully for each target. The targets are considered as multiple submissiles separated from the missile. Simulation results shows the performance of the proposed algorithm.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1195-1198
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• 2003

Micro former has been known as a useful tool for machining micro parts. It makes micro holes automatically with punches, a hole-shape die and material by rotation of crank shaft synchronously. Micro displacement in micro forming affects on the performance of machining because micro forming size is similar with its mechanical displacement. Therefore, the measurement of this micro displacement is essential to be guaranteed to obtain high forming precision in the whole machine as well as its devices. This paper addresses the development of a laser interferometer to measure micro displacement for a micro former. The laser interferometer is able to measure micro displacement during a few micro seconds with non-contact. For the experiment, a laser probe is installed on the optical table with optical devices and a micro displacement generating device. The velocity decoding board is also added to calculate doppler shift frequency directly. Finally simple experiments are conducted to confirm its functional operation.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.5 no.2
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• pp.22-26
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• 2006

This paper addresses the development of a laser interferometer to measure micro displacement for a micro system. The laser interferometer is able to measure micro displacement during a few micro seconds with non-contact. In order to employ the interferometer, the displacement calibration experiment should be required. For the experiment, a laser probe installed on the optical table with optical devices and a micro stage. The velocity decoding board is also added to calculate doppler shift frequency directly. The output signal is processed by LabView. Finally experiments are found out the relation between displacement and output signal.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.39-46
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• 2024

In this paper, we propose an efficient method for estimating the number of people and their locations using multiple IR-UWB radar sensors. Using three IR-UWB radar sensors in the indoor space, the measured signal from the target is processed to remove the clutter using rejection methods. Then, to further remove the clutter and to determine the presence of the human, the time-frequency image representing the micro-Doppler is obtained and classified by a convolutional neural network. Finally, the system finds the number of human objects and estimates each position in a two-dimensional space. In experiments using the measured data, the system successfully estimated the location and number of individuals with a high accuracy ≈ 88.68 %.