FM Signal Feature Extraction Using FFT-Based Integrated Interpolation Frequency Estimator

Feature extraction of FM signal is the first and most important step in modern automatic communication signal recognition. Based on the real-world collected silent FM observation, a systematic method for feature extraction of FM signal is presented after an intensive experiment modeling analysis, wh...

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Bibliographic Details
Main Authors: Yuchun, Huang, Zailu, Huang, Benxiong, Huang, Shuhua, Xu
Format: Conference Proceeding
Language:English
Subjects:
Application software
Computational modeling
Computer simulation
Feature extraction
FFT
FM signal
Frequency estimation
Integrated Interpolation Frequency Estimator
Interpolation
Maximum likelihood estimation
Parameter estimation
Robustness
Signal analysis
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Summary:Feature extraction of FM signal is the first and most important step in modern automatic communication signal recognition. Based on the real-world collected silent FM observation, a systematic method for feature extraction of FM signal is presented after an intensive experiment modeling analysis, which includes Hilbert Transform and the key robust single-tone parameter estimation technique---FFT-based Integrated Interpolation Frequency Estimator (IIFE) which integrates the contribution of more FFT coefficients than traditional FFT-based estimators in single tone frequency estimation through a novel normalized frequency offset estimation moving average model and Maximum Likelihood estimation. Computer Monte-Caro simulations show the performance of estimator approximates the CRLB closely even at as low SNR as -9dB at 256 FFT points with little addition of computation time compared to traditional FFT-based ones and that the proposed IIFE is effective in its application to feature extraction of FM signal.
ISSN:2155-7578
2155-7586
DOI:10.1109/MILCOM.2007.4455090