Woo-Yong Yang

Extraction of jet engine modulation component weakly present in measured signals for enhanced radar target recognition

This study presents a method for extracting the jet engine modulation (JEM) component weakly present in the radar received signal. First, the analytic form of the complicated measured signal is decomposed into intrinsic mode functions (IMFs) via complex empirical mode decomposition (CEMD). Then, the extracted IMFs are combined to reconstruct the JEM component based on the signal eccentricity, which serves as assessing the JEM micro-Doppler contribution to the signal. Applying these techniques to the measured raw signals demonstrate that the proposed extraction method significantly improves the clarity of the JEM analysis and is expected to be useful for enhanced radar target recognition.

Extraction of vibration components from a rotating propeller model based on complex empirical mode decomposition

In this paper, we present extraction of vibration components embedded in signatures from rotating propellers. In order to deal with complex-valued signatures, complex empirical mode decomposition (CEMD), an extended version of EMD, is employed to extract the vibration components. With FEKO simulation, we obtain composite signatures induced by both rotation and vibration of the simply modeled propeller for two different cases. Then CEMD is applied to these signatures and the reconstructed vibration components are analyzed in the joint time-frequency domain. The estimated vibration-related parameters showed reasonable agreement with actual motion parameters. This paper shows good possibility of predicting new characteristics from rotating propellers.

Automatic feature extraction from insufficient JEM signals based on compressed sensing method

This paper presents an automatic feature extraction from insufficient JEM signals based on compressed sensing (CS) method. First, the CS method was employed to extract a refined spectrum from insufficient JEM signals. In the process of applying the CS method to JEM signals, we utilized the modified linear programming (LP) standard form of an optimization method. After converting the spectrum into the time domain signal using the inverse Fourier transform (IFT), the cepstrum function was used for acquiring the spool rate. Then, the blade domain signal can be obtained by rounding off operation after dividing the reconstructed frequencies by the spool rate. Finally, the final blade number was extracted based on the divisor-multiplier (DM) rule and the scoring concept. Its application to insufficient JEM signals demonstrated that the automatic feature extraction method improved the accuracy of JEM analysis and is expected to be effective from the perspective of radar resource management.

Efficient Acquisition of High-Quality ISAR Images Using the Discrete Gabor Representation in an Oversampling Scheme

Inverse synthetic aperture radar(ISAR) images have been widely used in non-cooperative target recognition(NCTR). One of the most important issues in ISAR imaging is the improvement of the image smeared by target motion. In this paper, we propose the discrete Gabor representation(DGR) in an oversampling scheme for efficient acquisition of high-quality ISAR images. The DGR compartmentally assigns the Gabor coefficients to unit cells of the time-frequency grid related to the given Gabor logons. Thus, it can show an excellent time-frequency concentration and effectively discriminates the Doppler components from point-scatterers. The simulation results demonstrated that the DGR not only

Localization of Jet Engine Position from HRRP-JEM Images of Aircraft Targets Using Eccentricity of Complex-Valued Signals

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.