Contributions to Proceedings:

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, 642 - 645.

English abstract:
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.

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

Electronic version of the publication:

Related Projects:
Project Head Franz Hlawatsch:
Signal and Information Processing in Science and Engineering - Statistische Inferenz

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