[Zurück]


Beiträge in Tagungsbänden:

A. Jung, G. Tauböck, F. Hlawatsch:
"Compressive Nonstationary Spectral Estimation Using Parsimonious Random Sampling of the Ambiguity Function";
in: "Proc. IEEE SSP-09", IEEE Conference Proceedings, 2009, S. 642 - 645.



Kurzfassung englisch:
We propose a compressive estimator for the discrete Rihaczek spectrum
(RS) of a time-frequency sparse, underspread, nonstationary
random process. The new estimator uses a compressed sensing technique
to achieve a reduction of the number of measurements. The
measurements are randomly located samples of the ambiguity function
of the observed signal. We provide a bound on the mean-square
estimation error and demonstrate the performance of the estimator
by means of simulation results. The proposed RS estimator can also
be used for estimating the Wigner-Ville spectrum (WVS) since for
an underspread process the RS and WVS are almost equal.

Schlagworte:
Basis Pursuit, Compressed Sensing, Nonstationary Spectral Estimation, Rihaczek Spectrum, Wigner Ville Spectrum


Elektronische Version der Publikation:
http://publik.tuwien.ac.at/files/PubDat_177502.pdf



Zugeordnete Projekte:
Projektleitung Franz Hlawatsch:
Signal and Information Processing in Science and Engineering - Statistische Inferenz


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.