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ICASSP
2009
IEEE

Compressive spectral estimation for nonstationary random processes

10 years 4 months ago
Compressive spectral estimation for nonstationary random processes
We propose a “compressive” estimator of the Wigner-Ville spectrum (WVS) for time-frequency sparse, underspread, nonstationary random processes. A novel WVS estimator involving the signal’s Gabor coefficients on an undersampled time-frequency grid is combined with a compressed sensing transformation in order to reduce the number of measurements required. The performance of the compressive WVS estimator is analyzed via a bound on the mean square error and through simulations. We also propose an efficient implementation using a special construction of the measurement matrix.
Alexander Jung, Georg Tauböck, Franz Hlawatsc
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Alexander Jung, Georg Tauböck, Franz Hlawatsch
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