Computationally efficient algorithms for cyclic spectral analysis

Two computationally efficient algorithms for digital cyclic spectral analysis, the FFT accumulation method (FAM) and the strip spectral correlation algorithm (SSCA), are developed from a series of modifications on a simple time smoothing algorithm. The signal processing, computational, and structural attributes of time smoothing algorithms are presented with emphasis on the FAM and SSCA. As a vehicle for examining the algorithms the problem of estimating the cyclic cross spectrum of two complex-valued sequences is considered. Simplifications of the resulting expressions to special cases of the cross cyclic spectrum of two complex-valued sequences, such as the cyclic spectrum of a single real-valued sequence, are easily found. Computational and structural simplifications arising from the specialization are described.<>