• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.12
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• pp.1173-1180
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• 2013

High Resolution Range Profile-Jet Engine Modulation imagery first introduced in 2005 carries out radar target recognition by localizing the position of the jet engine installed on the aircraft target. This paper presents a new approach for estimating the jet engine position in the HRRP-JEM image based on the eccentricity of a complex signal. It can effectively evaluate the contribution of the JEM component to the radar received signal in a range bin of the HRRP-JEM image. Therefore, the localization is expected to be performed more quantitatively and reliably by pinpointing the range bin corresponding to the jet engine position where the JEM contribution is maximized. The simulation results of realistic aircraft models validated the effectiveness of the proposed concept.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.3
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• pp.217-224
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• 2017

In this paper, we propose a fusion classification method combining HRRP and JEM classifier with complementary properties for the classification of aircraft. The fusion method is based on the confidence of a classifier for a classification result to improve performance compared with single classifier in various situations. The confidence is defined as the posterior probability estimated from the classification performance of a classifier and it depends on the aspect angle and the certainty for a classification result. Through the classification test using simulation data, we can verify that the proposed fusion method shows good performance by fusing the classifiers effectively.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.3
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• pp.252-259
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• 2019

Jet engine modulation(JEM) signals are widely used in the field of target recognition along with high-range resolution profile and inverse synthetic aperture radar because they provide specific information of the jet engine. To obtain the number of blades of the jet engine, the chopping frequency proportional to the number of blades must be extracted. In the conventional chopping frequency extraction method, an initial threshold value is defined and a method of detecting the chopping peak is used. However, this detection method takes time depending on the signal due to repetitive detection. Thus, in this study, we proposed to extract the chopping frequency using MUltiple SIgnal Classification(MUSIC) algorithm. We applied the MUSIC algorithm to a given JEM signal to find the chopping frequency and determine the blade number candidates. We also applied the MUSIC algorithm to other chopping frequency extractions to determine the score of the candidate groups. Unlike the conventional detection algorithm, which requires repetitive frequency detection, MUSIC algorithm quickly detects the accurate chopping frequency and reduces the calculation time.