Extraction of jet engine parameters from micro‐Doppler signatures using continuous wavelet transform

Abstract

Abstract Micro‐Doppler signatures in jet engine modulated (JEM) radar signals are used to extract jet engine features for automatic target recognition. Herein, a novel algorithm based on the continuous wavelet transform (CWT) is used to determine the spool rate and the number of blades of a jet engine. The return signal is represented at multiple scales to form a scalogram for time‐frequency analysis. Further, the energy of the scalogram across various scales is computed and salient local maxima in the energy plot are extracted. The signals are analysed at the corresponding scales of salient local maxima and are used to extract spool rate and chopping frequency. The algorithm is applied to the simulated JEM signals affected by noise and investigated using Coiflet and complex Morlet wavelets. In the presence of noise, the proposed algorithm using both the wavelets has shown better performance when compared with the modified Hilbert Huang Transform (HHT) algorithm.