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Sparse Semi-Parametric Chirp Estimator

Swärd, Johan LU ; Brynolfsson, Johan LU ; Jakobsson, Andreas LU orcid 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:
author
; ; and
organization
publishing date
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
2022-01-29 21:41:47
@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}},
}