Adaptive Detection of a Partly Known Signal Corrupted by Strong Interference
(2011) In IEEE Signal Processing Letters 18(12). p.729-732- Abstract
- In this letter, we consider adaptive detection of a partly known signal corrupted by additive noise and strong interference with support that is only partly known. Assuming a homogeneous environment where the covariance matrix of the additive noise is the same for the primary and secondary data sets, although with the secondary data set also being affected by the interference, we allow for conic uncertainty models for both the signal and interference subspaces, developing a generalized likelihood ratio detector for the signal of interest. Numerical examples indicate that the proposed method offers a notable performance gain as compared to other recent related methods.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2214243
- author
- Svensson, Albin and Jakobsson, Andreas LU
- organization
- publishing date
- 2011
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- uncertainty, strong interference, signal detection, Iterative methods
- in
- IEEE Signal Processing Letters
- volume
- 18
- issue
- 12
- pages
- 729 - 732
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- wos:000296469700002
- scopus:80455137051
- ISSN
- 1070-9908
- DOI
- 10.1109/LSP.2011.2172421
- language
- English
- LU publication?
- yes
- id
- 919e9bc5-c559-4c20-bc7b-7bb1a8643804 (old id 2214243)
- date added to LUP
- 2016-04-04 09:52:53
- date last changed
- 2022-02-21 02:18:56
@article{919e9bc5-c559-4c20-bc7b-7bb1a8643804, abstract = {{In this letter, we consider adaptive detection of a partly known signal corrupted by additive noise and strong interference with support that is only partly known. Assuming a homogeneous environment where the covariance matrix of the additive noise is the same for the primary and secondary data sets, although with the secondary data set also being affected by the interference, we allow for conic uncertainty models for both the signal and interference subspaces, developing a generalized likelihood ratio detector for the signal of interest. Numerical examples indicate that the proposed method offers a notable performance gain as compared to other recent related methods.}}, author = {{Svensson, Albin and Jakobsson, Andreas}}, issn = {{1070-9908}}, keywords = {{uncertainty; strong interference; signal detection; Iterative methods}}, language = {{eng}}, number = {{12}}, pages = {{729--732}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Signal Processing Letters}}, title = {{Adaptive Detection of a Partly Known Signal Corrupted by Strong Interference}}, url = {{http://dx.doi.org/10.1109/LSP.2011.2172421}}, doi = {{10.1109/LSP.2011.2172421}}, volume = {{18}}, year = {{2011}}, }