A generalized stochastic resonance based instantaneous frequency estimation method under low SNR. (1st February 2022)

• Record Type: Journal Article
• Authors: Liu, Yang; Xiong, Zhenhua
• Is Part Of: Mechanical systems and signal processing. Volume 164(2022)
• Publication Date: 2022-02-01
• Subjects: Instantaneous frequency estimation -- Frequency modulated signal -- Low SNR -- Generalized stochastic resonance -- Optimization; SNR signal-to-noise ratio -- IF instantaneous frequency -- FM frequency modulated -- SR stochastic resonance -- GSR generalized stochastic resonance -- TF time–frequency -- TFR time–frequency representation -- STFT short time Fourier transform -- CWT continuous wavelet transform -- WVD Wigner Ville distribution -- ACO ant colony optimization -- ML maximum likelihood -- QML quasi-maximum-likelihood -- RCIF ridge curve iterative fitting -- GA genetic algorithm -- LPF low pass filter -- MSE mean square error; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.108269
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: The GSR method is proposed to enhance the weak frequency-modulated signals. The instantaneous frequency is estimated by global optimization based on the GSR output signal. The proposed method greatly improves the IF estimation accuracy under low SNR below −25 dB. Abstract: In this work, the instantaneous frequency estimation for the frequency modulated (FM) signal embedded in strong noise is considered. For engineering signals, current instantaneous frequency estimation methods are less satisfactory under low signal-to-noise ratio (SNR). To address this problem, a generalized stochastic resonance (GSR) based instantaneous frequency estimation method is proposed. First, the generalized stochastic resonance (GSR) is proposed, which overcomes the low frequency limitation of classical stochastic resonance and can enhance weak FM signals with time varying frequency. The GSR transforms the FM signal to a low-constant frequency signal by multiplying the parameterized demodulation operator with polynomial phase and then enhances it by the stochastic resonance. Second, based on the maximization of the GSR output signal, the instantaneous frequency can be estimated by global optimization of the polynomial coefficients in the parametrized demodulation operator. For the multi-component FM signal, it works by enhancing the objective component and suppressing the noise and other irrelevant components, in which the instantaneous frequency of each component is estimated in the order of component strengths and each component can be extracted from the signal. Numerical simulations and experimental signals validate that the proposed method outperforms the state-of-art methods in estimation accuracy for both mono-component and multi-component FM signals under lower SNR.