Phased Fractional Lower-Order Cyclic Moment Processed in Compressive Signal Processing

In signal processing research, cyclostationarity and fractional lower-order statistics (FLOS) are two important solutions to non-stationary signals and non-Gaussian noises, respectively. In the last five years, many methodologies combining the two technologies were proposed to achieve the two tasks...

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Bibliographic Details
Published in:IEEE access 2019, Vol.7, p.98811-98819
Main Authors: Liu, Tao, Qiu, Tianshuang, Jin, Fangxiao, Wilcox, Stephanie, Luan, Shengyang
Format: Article
Language:English
Subjects:
Compressed sensing
compressive sensing
compressive signal processing
Correlation
Cyclostationarity
Fourier transforms
fractional lower-order statistics
Frequency-domain analysis
Gaussian process
non-Gaussian noise
Parameter estimation
Parameter identification
Sampling
Signal detection
Signal processing
Sparse matrices
System identification
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Summary:In signal processing research, cyclostationarity and fractional lower-order statistics (FLOS) are two important solutions to non-stationary signals and non-Gaussian noises, respectively. In the last five years, many methodologies combining the two technologies were proposed to achieve the two tasks simultaneously. Unfortunately, these methodologies need to be based on the Shannon/Nyquist sampling theorem. As phased fractional lower-order cyclic moment (PFLOCM) theoretically cooperates with compressive signal processing (CSP), this paper studies PFLOCM to apply in CSP at sub-Nyquist sampling rates. Using this technical foundation, a complete procedure is novelly proposed to rebuild phased fractional lower-order cyclic moment spectrum (PFLOCMS), which functions as a crucial factor in signal detection, system identification, parameter estimation, and other applications. In addition, various experiments verify the performance of the proposed procedure. It is believed that this paper will have implications for non-stationary and non-Gaussian signal processing at sub-Nyquist sampling rates.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2929434