Estimation of chirp signals with time-varying amplitudes
(2018) In Signal Processing 147. p.1-10- Abstract
The problem of parameters estimation of signals composed of an unknown number of chirps with time-varying amplitude is presented using a sparse reconstruction framework. The method employs a parametric model using a weighted combination of splines to model the time-varying nature of the signal amplitudes. To obtain high-resolution of the frequencies and to avoid large dimensional matrices, a dictionary refinement technique is employed. The method can accurately estimate the amplitude and frequency parameters of multiple signal components, and may be extended to allow for non-linear chirps. Furthermore, an efficient implementation to solve the resulting optimization problem is proposed. Results on both synthetic and experimental signals... (More)
The problem of parameters estimation of signals composed of an unknown number of chirps with time-varying amplitude is presented using a sparse reconstruction framework. The method employs a parametric model using a weighted combination of splines to model the time-varying nature of the signal amplitudes. To obtain high-resolution of the frequencies and to avoid large dimensional matrices, a dictionary refinement technique is employed. The method can accurately estimate the amplitude and frequency parameters of multiple signal components, and may be extended to allow for non-linear chirps. Furthermore, an efficient implementation to solve the resulting optimization problem is proposed. Results on both synthetic and experimental signals illustrate the efficient performance of the algorithm.
(Less)
- author
- Meng, Xiangxia ; Jakobsson, Andreas LU ; Li, Xiukun and Lei, Yahui
- organization
- publishing date
- 2018-06-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- ADMM, Chirp signals, Sparse reconstruction, Time-varying amplitude
- in
- Signal Processing
- volume
- 147
- pages
- 10 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:85041490413
- ISSN
- 0165-1684
- DOI
- 10.1016/j.sigpro.2018.01.017
- language
- English
- LU publication?
- yes
- id
- 74829d11-7048-42aa-a2c8-dab4a2062b6b
- date added to LUP
- 2018-02-20 08:28:15
- date last changed
- 2022-04-25 05:38:51
@article{74829d11-7048-42aa-a2c8-dab4a2062b6b, abstract = {{<p>The problem of parameters estimation of signals composed of an unknown number of chirps with time-varying amplitude is presented using a sparse reconstruction framework. The method employs a parametric model using a weighted combination of splines to model the time-varying nature of the signal amplitudes. To obtain high-resolution of the frequencies and to avoid large dimensional matrices, a dictionary refinement technique is employed. The method can accurately estimate the amplitude and frequency parameters of multiple signal components, and may be extended to allow for non-linear chirps. Furthermore, an efficient implementation to solve the resulting optimization problem is proposed. Results on both synthetic and experimental signals illustrate the efficient performance of the algorithm.</p>}}, author = {{Meng, Xiangxia and Jakobsson, Andreas and Li, Xiukun and Lei, Yahui}}, issn = {{0165-1684}}, keywords = {{ADMM; Chirp signals; Sparse reconstruction; Time-varying amplitude}}, language = {{eng}}, month = {{06}}, pages = {{1--10}}, publisher = {{Elsevier}}, series = {{Signal Processing}}, title = {{Estimation of chirp signals with time-varying amplitudes}}, url = {{http://dx.doi.org/10.1016/j.sigpro.2018.01.017}}, doi = {{10.1016/j.sigpro.2018.01.017}}, volume = {{147}}, year = {{2018}}, }