Computationally Efficient Robust Adaptive Beamforming for Passive Sonar
(2015) Underwater Defence Technology (UDT 2015)- Abstract
- Recent work has highlighted the benefits of exploiting robust
Capon beamformer (RCB) techniques in passive sonar.
Unfortunately, the computational requirements for computing
the standard RCB weights are cubic in the number of
adaptive degrees of freedom, which may be computationally
prohibitive in practical situations. Here, we examine recent
computationally efficient techniques for computing the RCB
weights and evaluate their performances for passive sonar.
We also discuss the implementation of these efficient algorithms
on parallel architectures, such as graphics processing
units (GPUs), illustrating that further significant speed-ups
are... (More) - Recent work has highlighted the benefits of exploiting robust
Capon beamformer (RCB) techniques in passive sonar.
Unfortunately, the computational requirements for computing
the standard RCB weights are cubic in the number of
adaptive degrees of freedom, which may be computationally
prohibitive in practical situations. Here, we examine recent
computationally efficient techniques for computing the RCB
weights and evaluate their performances for passive sonar.
We also discuss the implementation of these efficient algorithms
on parallel architectures, such as graphics processing
units (GPUs), illustrating that further significant speed-ups
are possible over a central processing unit (CPU) based implementation. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7767415
- author
- Somasundaram, Samuel ; Pilkington, Adrian ; Hart, Leslie ; Butt, Naveed LU and Jakobsson, Andreas LU
- organization
- publishing date
- 2015
- type
- Contribution to conference
- publication status
- published
- subject
- keywords
- Passive sonar, computationally efficient robust adaptive beamforming.
- conference name
- Underwater Defence Technology (UDT 2015)
- conference location
- Rotterdam, Netherlands
- conference dates
- 2015-06-03 - 2015-06-05
- language
- English
- LU publication?
- yes
- id
- e6e5583d-eda4-445b-b9ba-1246f3fca203 (old id 7767415)
- date added to LUP
- 2016-04-04 14:37:33
- date last changed
- 2019-03-08 02:33:54
@misc{e6e5583d-eda4-445b-b9ba-1246f3fca203, abstract = {{Recent work has highlighted the benefits of exploiting robust<br/><br> Capon beamformer (RCB) techniques in passive sonar.<br/><br> Unfortunately, the computational requirements for computing<br/><br> the standard RCB weights are cubic in the number of<br/><br> adaptive degrees of freedom, which may be computationally<br/><br> prohibitive in practical situations. Here, we examine recent<br/><br> computationally efficient techniques for computing the RCB<br/><br> weights and evaluate their performances for passive sonar.<br/><br> We also discuss the implementation of these efficient algorithms<br/><br> on parallel architectures, such as graphics processing<br/><br> units (GPUs), illustrating that further significant speed-ups<br/><br> are possible over a central processing unit (CPU) based implementation.}}, author = {{Somasundaram, Samuel and Pilkington, Adrian and Hart, Leslie and Butt, Naveed and Jakobsson, Andreas}}, keywords = {{Passive sonar; computationally efficient robust adaptive beamforming.}}, language = {{eng}}, title = {{Computationally Efficient Robust Adaptive Beamforming for Passive Sonar}}, url = {{https://lup.lub.lu.se/search/files/6403669/7767416.pdf}}, year = {{2015}}, }