The concern here is of retrieving damped harmonics and polynomial phase signals in the presence of additive noise. The damping function is not limited to the exponential model, and in certain cases, the additive noise does not have to be white. Three classes of algorithms are presented, namely DFT based, Kumaresan-Tufts type extensions, and subspace variants including the MUSIC algorithm. Preference should be based on the available data length and frequency separations. In addition, retrieval of self coupled damped harmonics, which may be present when nonlinearities exist in physical systems, is investigated. Simulation examples illustrate main points of the paper.

Date Published: 28 October 1994
PDF: 12 pages
Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); doi: 10.1117/12.190835

Published in SPIE Proceedings Vol. 2296:
Advanced Signal Processing: Algorithms, Architectures, and Implementations V
Franklin T. Luk, Editor(s)