Sparse Semi-Parametric Chirp Estimator
Swärd, Johan LU ; Brynolfsson, Johan LU ; Jakobsson, Andreas LU
and Sandsten, Maria
LU
(2015)
48th Asilomar Conference on Signals, Systems and Computers, 2014
p.1236-1240
- Abstract
- In this work, we present a method for estimating the parameters detailing an unknown number of linear chirp signals, using an iterative sparse reconstruction framework. The proposed method is initiated by a re-weighted Lasso approach, and then use an iterative relaxation-based refining step to allow for high resolution estimates. The resulting estimates are found to be statistically efficient, achieving the Cramér-Rao lower bound. Numerical simulations illustrate the achievable performance, offering a notable improvement as compared to other recent approaches.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7860309
- author
- Swärd, Johan
LU
; Brynolfsson, Johan
LU
; Jakobsson, Andreas
LU
and Sandsten, Maria
LU
- organization
- publishing date
- 2015-04-27
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Signals, Systems and Computers, 2014 48th Asilomar Conference on
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 48th Asilomar Conference on Signals, Systems and Computers, 2014
- conference location
- Pacific Grove, California, United States
- conference dates
- 2014-11-02 - 2014-11-05
- external identifiers
-
- scopus:84940505837
- ISBN
- 978-1-4799-8295-0
- DOI
- 10.1109/ACSSC.2014.7094656
- language
- English
- LU publication?
- yes
- id
- 4dc0cd93-f5ec-4c97-af42-77e3a576a125 (old id 7860309)
- date added to LUP
- 2016-04-04 11:19:34
- date last changed
- 2025-10-14 11:30:44
@inproceedings{4dc0cd93-f5ec-4c97-af42-77e3a576a125,
abstract = {{In this work, we present a method for estimating the parameters detailing an unknown number of linear chirp signals, using an iterative sparse reconstruction framework. The proposed method is initiated by a re-weighted Lasso approach, and then use an iterative relaxation-based refining step to allow for high resolution estimates. The resulting estimates are found to be statistically efficient, achieving the Cramér-Rao lower bound. Numerical simulations illustrate the achievable performance, offering a notable improvement as compared to other recent approaches.}},
author = {{Swärd, Johan and Brynolfsson, Johan and Jakobsson, Andreas and Sandsten, Maria}},
booktitle = {{Signals, Systems and Computers, 2014 48th Asilomar Conference on}},
isbn = {{978-1-4799-8295-0}},
language = {{eng}},
month = {{04}},
pages = {{1236--1240}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Sparse Semi-Parametric Chirp Estimator}},
url = {{https://lup.lub.lu.se/search/files/5747546/7860310.pdf}},
doi = {{10.1109/ACSSC.2014.7094656}},
year = {{2015}},
}