Robust and fast algorithm for extracting the periodic feature from jet engine modulation signals

Abstract

Jet engine modulation (JEM), a modulation phenomenon induced by the rotating structure of jet engines, is a representative feature extracted from the radar returns for aircraft target recognition. As one of the most significant periodic characteristics of JEM, the chopping frequency plays an important role in aircraft target recognition. However, existing methods either need complicated logical algorithms to get an accurate estimation of the chopping frequency or exploit the chopping frequency as priori information for further feature extraction, and neither of these two scenarios is practical. Here, the authors propose a robust and fast algorithm for extracting the chopping frequency, which uses wavelet decomposition combined with autocorrelation to process the analytic form of the JEM signal. Application results of measured JEM signals demonstrate that the proposed algorithm is effective and practical for stable and accurate extraction of the periodic feature from JEM signals.