Abstract
Multicomponent sinusoidal frequency modulated (SFM) signals are widely used in radar, acoustics, and biomedicine. The instantaneous frequency (IF) characterizes important physical parameters of the real applications. In this paper, a sinusoidal frequency modulation Fourier-Bessel (SFMFB) series is defined for IF estimation. It provides the signal decomposition on the Bessel function basis with a finer resolution, which proposes an extension of the performance and the applicability of the classic Fourier-Bessel transform (FBT). Based on the property analysis of the SFMFB series, an algorithm of IF estimation and signal separation is introduced. Unlike the existing estimation methods which apply sliding windows to make an instantaneous approximation, the proposed method uses the global data, which provides a longer period gain, therefore achieving a better estimation performance. Moreover, considering that most estimation methods are invalid in multicomponent separation, the individual signals are well separated by the proposed algorithm, which facilitates the further monocomponent analysis. A performance comparison between the proposed method, the FBT, and another recently proposed sinusoidal frequency modulation Fourier transform (SFMFT) is also provided. Simulation results indicate that the proposed method outperforms the existing methods in estimation precision and computation load, and it is free of interference which exists in SFMFT.
Highlights
Multicomponent sinusoidal frequency modulated (SFM) signals have been widely used in various real-life applications such as radar target recognition, speech analysis, and biomedical disease diagnosis [1,2,3,4]
As the spectral contents of the SFM signals vary with time, the frequency at a particular time is well described by the instantaneous frequency (IF)
Considering the existing problems of the IF estimation on the Bessel domain, this paper proposes an extension of the estimation performance as well as the applicability of the classic FourierBessel transform (FBT) and the FB series in IF estimation of multicomponent SFM signals
Summary
Multicomponent sinusoidal frequency modulated (SFM) signals have been widely used in various real-life applications such as radar target recognition, speech analysis, and biomedical disease diagnosis [1,2,3,4]. Instead of constructing parametric models or equations, the TFD based methods analyze the time-frequency features of a signal first and the IF is estimated by tracking their periodical features [5,6,7] In these methods, the length of the time window is one of the most important parameters. A sinusoidal frequency modulation Fourier-Bessel (SFMFB) series is defined, the properties of the SFMFB series are derived, and a novel IF estimation and signal separation approach for multicomponent SFM signals is introduced via the property analysis.
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