• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.129-138
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• 2017

This paper has been shown for the extraction of Doppler signature from the radar signal for an air-breathing targets tracked in the ground radar. For the extractions, a Doppler resolution is confirmed from mathematical modeling of PT(pulse train) waveform. Doppler signatures of air-breathing target are varied to radar aspect angle of engine and are determined from physical parameter of jet engine. To confirm such Doppler signatures, the radar signal reflected from the air-breathing target is obtained by our radar signal storage. After this extraction, radar aspect angle of engine has estimated from tracking information. Relative differences of Doppler signatures to radar aspect angle of engine is verified from these results and Doppler profiles for radar target identification appliance are presented.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1E
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• pp.25-30
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• 2001

The unstable signature that is defined as frequency change with respect to the time or frequency modulation, is caused by the external loading variation in specific machinery component and Doppler shift etc. In this study, we analyze the generation mechanism of the unstable signature and apply the Extended Kalman filter (EKF) algorithm for its detection. The performance of Extended Kalman Filter is examined for numerical and measured signals and the results show its validity for unstable signature detection.

• 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.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.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.446-454
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• 2002

This paper presents the Doppler Scanning technique which enables us to detect the relative positions of moving distributed sources using Doppler frequency shift estimate when the moving source consists of distributed sources with different signature frequencies. Doppler frequency shifts of characteristic frequencies of machinery noise sources such as ship's generator and propeller, with tine along CPA (Closest Point of Approach of moving source) are unique, and can be functioned with respect to each source position. Therefore, this technique can be applied to estimate the relative geometrical positions between machinery noise sources. The Extended Kalman Filter (EKF) which has a high frequency resolution with high time resolution, is adopted for improving accuracy of Doppler frequency shift estimate geometric resolution of machinery positions since machinery noise sources show in general low frequency band characteristics with limited spacial distance. The performance of the technique is examined by the numerical simulations and is verified by the experiment using loudspeaker sources on the roof of the car.

• 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 KIEE Conference
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• 1998.07b
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• pp.657-659
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• 1998

In this paper we discuss an algorithm to discriminate a target under track against multiple acoustic counter-measure (ACM) sources, based on sequential testings of multiple hypotheses. The ACM sources are separated from the target under track and generate, while drifting, measurements with false range and Doppler information. The purpose of the ACM is to mislead the target tracking and to help the true target evade a pursuer. The proposed algorithm uses as a test statistic a function of both the sequences of processed waveform signature and the innovation sequences from extended Kalman filters to estimate the target dynamics and the drifting positions of the ACM sources. Numerical experiments on various scenarios show that the proposed algorithm discriminates the target faster with a higher probability of success than the algorithm using only the innovation sequences from extended Kalman filters.