Integrated FFT-Based Interpolation Frequency Estimator and its Application to Feature Extraction of FM Signal

Feature extraction of FM signal is the first and most important step in modern automatic communication signal recognition. Based on the real-world collected FM signal, a systematic method for feature extraction of FM signal is presented after an intensive experiment modeling analysis, which includes Hilbert Transform and the key single-tone parameter estimation technique-integrated FFT-based interpolation frequency estimator (IIFE) by integrating the contribution of more FFT coefficients than traditional FFT-based estimators in the frequency estimation of single tone through a novel normalized frequency offset estimation model and maximum likelihood estimation. Computer Monte-Carlo simulations show the proposed IIFE outperforms traditional FFT-based ones with little addition of computation time, which is very effective in its application to feature extraction of FM signal.