Monostatic MIMO radar direction finding in impulse noise
(2021) In Digital Signal Processing: A Review Journal 117.- Abstract
This work considers direction-finding using a monostatic multiple-input multiple-output (MIMO) radar in the presence of impulsive noise. Employing a novel low-order covariance-based exponential kernel function, the proposed maximum likelihood (ML) formulation exploits an introduced quantum whale optimization algorithm (QWOA) to form the direction estimates. The resulting estimates are shown to be robust to the presence of impulsive noise, offering preferable performance as compared to recent related approaches, even in cases when the number of available snapshots is small.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/ddd07274-6161-40bd-b33e-422c37e5c0fa
- author
- Gao, Hongyuan ; Chen, Menghan LU ; Du, Yanan and Jakobsson, Andreas LU
- organization
- publishing date
- 2021
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Cramér-Rao bound, Direction-finding, Impulse noise, Maximum likelihood method, Monostatic MIMO radar
- in
- Digital Signal Processing: A Review Journal
- volume
- 117
- article number
- 103198
- publisher
- Elsevier
- external identifiers
-
- scopus:85113155553
- ISSN
- 1051-2004
- DOI
- 10.1016/j.dsp.2021.103198
- language
- English
- LU publication?
- yes
- id
- ddd07274-6161-40bd-b33e-422c37e5c0fa
- date added to LUP
- 2021-09-07 13:27:43
- date last changed
- 2022-04-27 03:42:27
@article{ddd07274-6161-40bd-b33e-422c37e5c0fa, abstract = {{<p>This work considers direction-finding using a monostatic multiple-input multiple-output (MIMO) radar in the presence of impulsive noise. Employing a novel low-order covariance-based exponential kernel function, the proposed maximum likelihood (ML) formulation exploits an introduced quantum whale optimization algorithm (QWOA) to form the direction estimates. The resulting estimates are shown to be robust to the presence of impulsive noise, offering preferable performance as compared to recent related approaches, even in cases when the number of available snapshots is small.</p>}}, author = {{Gao, Hongyuan and Chen, Menghan and Du, Yanan and Jakobsson, Andreas}}, issn = {{1051-2004}}, keywords = {{Cramér-Rao bound; Direction-finding; Impulse noise; Maximum likelihood method; Monostatic MIMO radar}}, language = {{eng}}, publisher = {{Elsevier}}, series = {{Digital Signal Processing: A Review Journal}}, title = {{Monostatic MIMO radar direction finding in impulse noise}}, url = {{http://dx.doi.org/10.1016/j.dsp.2021.103198}}, doi = {{10.1016/j.dsp.2021.103198}}, volume = {{117}}, year = {{2021}}, }