Sparse Semi-Parametric Estimation of Harmonic Chirp Signals

In this paper, we present a method for estimating the parameters detailing an unknown number of linear, possibly harmonically related, chirp signals, using an iterative sparse reconstruction framework. The proposed method is initiated by a re-weighted group-sparsity approach, followed by an iterativ...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2016-04, Vol.64 (7), p.1798-1807
Main Authors: Sward, Johan, Brynolfsson, Johan, Jakobsson, Andreas, Hansson-Sandsten, Maria
Format: Article
Language:English
Subjects:
block sparsity
Chirp
Cramér-Rao lower bound
Electrical Engineering, Electronic Engineering, Information Engineering
Elektroteknik och elektronik
Engineering and Technology
Estimation
Harmonic analysis
Harmonic chirps
LASSO
multi-component
Signal Processing
Signal processing algorithms
Signal resolution
Signalbehandling
Teknik
Time-frequency analysis
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Summary:In this paper, we present a method for estimating the parameters detailing an unknown number of linear, possibly harmonically related, chirp signals, using an iterative sparse reconstruction framework. The proposed method is initiated by a re-weighted group-sparsity approach, followed by an iterative relaxation-based refining step, to allow for high-resolution estimates. Numerical simulations illustrate the achievable performance, offering a notable improvement as compared to other recent approaches. The resulting estimates are found to be statistically efficient, achieving the corresponding Cramér-Rao lower bound.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2015.2507538