The information about intrapulse modulation is commonly used to augment data in electronic intelligence systems. However, increasingly popular nonlinear frequency modulated (NLFM) waveform is hardly ever distinguished as a separate waveform class by electronic support systems. In this paper a method of recognizing NLFM radar signal is presented. The algorithm is based on two novel features extracted from fractional Fourier transform (FrFT) and instantaneous frequency estimated via quasi-maximum-likelihood (QML) method. Moreover, the algorithm is designed to be resistant to the multipath effects, which are inherent to land-based intercept systems.
KEYWORDS: Radar signal processing, Radar, Signal to noise ratio, Frequency modulation, Fourier transforms, Electronic signals intelligence, Signal detection
The paper presents a novel method for NLFM radar signal instantaneous frequency estimation. Up to now there are only a few limited reports in this field. The method involves combined short-time Fourier transform and IF curve smoothing in time – frequency plane. The algorithm performs a fine estimation of instantaneous frequency of noise buried signals up to -3 dB. Due to FFT and simple filtering application, there is no high computational load needed. Simulation results indicate that the algorithm is robust and outperforms well-known phase differentiation method.
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