Automatic Target Recognition Using Jet Engine Modulation and Time-Frequency Transform

We propose a method to recognize targets by using the signature of jet engine modulation (JEM) generated by the rotating blades in jet engines. The method combines time-frequency transform, 2-dimensional (2D) principal component analysis, and a nearest-neighbor classifier. In simulations using five propellers composed of isotropic point scatterers, the proposed method was insensitive to signal-to-noise SNR variation; this insensitivity was a result of the effective 2D time-frequency feature and the noise suppression by the matched filter. In simulations using a reduced training database, the result was most sensitive to variation in the rotation velocity of the blades.