Detection and classification of cyclostationary signals via cyclic-HOS: a unified approach

Amod V. Dandawate; Georgios B. Giannakis

doi:10.1117/12.130939

30 November 1992 Detection and classification of cyclostationary signals via cyclic-HOS: a unified approach

Amod V. Dandawate, Georgios B. Giannakis

Proceedings Volume 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III; (1992) https://doi.org/10.1117/12.130939
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

Detection and classification of cyclostationary signals in noise of unknown distribution is addressed and novel tests for cyclostationarity are proposed. Both cases of known and unknown signal statistics are considered. The proposed approaches exploit the asymptotic normality of sample cyclic- cumulant and polyspectrum estimators for deriving asymptotically optimal X² tests. Simpler, but generally suboptimal versions are also presented. Simulations are performed to test the proposed algorithms and illustrate their insensitivity to any stationary noise as well as the ability of higher-than second-order schemes to suppress cyclostationary Gaussian interferences of unknown covariance.

Citation Download Citation

Amod V. Dandawate and Georgios B. Giannakis "Detection and classification of cyclostationary signals via cyclic-HOS: a unified approach", Proc. SPIE 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III, (30 November 1992); https://doi.org/10.1117/12.130939

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