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Low-Complexity Uncertainty-Set-Based Robust Adaptive Beamforming for Passive Sonar

Somasundaram, Samuel; Butt, Naveed LU ; Jakobsson, Andreas LU and Hart, Les (2015) In IEEE Journal of Oceanic Engineering
Abstract
Recent work has highlighted the potential benefits of exploiting ellipsoidal uncertainty-set-based robust Capon beamformer (RCB) techniques in passive sonar. Regrettably, the computational complexity required to form RCB weights is cubic in the number of adaptive degrees of freedom, which is often prohibitive in practice. For this reason, several low-complexity techniques for computing RCB weights, or equivalent worst case robust adaptive beamformer weights, have recently been developed. These techniques, whose complexities are only quadratic in the number of adaptive degrees of freedom, use gradient-based, reduced-dimension Krylov-subspace or Kalman-filtering methods. In this work, we review these techniques for passive sonar, analyzing... (More)
Recent work has highlighted the potential benefits of exploiting ellipsoidal uncertainty-set-based robust Capon beamformer (RCB) techniques in passive sonar. Regrettably, the computational complexity required to form RCB weights is cubic in the number of adaptive degrees of freedom, which is often prohibitive in practice. For this reason, several low-complexity techniques for computing RCB weights, or equivalent worst case robust adaptive beamformer weights, have recently been developed. These techniques, whose complexities are only quadratic in the number of adaptive degrees of freedom, use gradient-based, reduced-dimension Krylov-subspace or Kalman-filtering methods. In this work, we review these techniques for passive sonar, analyzing their complexities and evaluating them initially on simulated data. The best performing methods are then evaluated on two in-water recorded passive sonar data sets. One set, containing a strong controlled acoustic source, demonstrates the ability of the algorithms to protect against signal cancellation when pointing at the source, and their ability to reject the source when pointing away from it. The other data set, recorded during a period when the boat was accelerating, demonstrates the ability of the algorithms to operate in the presence of speed-induced noises. (Less)
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organization
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Contribution to journal
publication status
published
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in
IEEE Journal of Oceanic Engineering
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:84946944370
ISSN
0364-9059
DOI
10.1109/JOE.2015.2474495
language
English
LU publication?
yes
id
cf3d5dcb-84a3-4a98-9428-8387fe942cef (old id 8409943)
date added to LUP
2016-02-29 13:33:36
date last changed
2017-07-09 03:11:00
@article{cf3d5dcb-84a3-4a98-9428-8387fe942cef,
  abstract     = {Recent work has highlighted the potential benefits of exploiting ellipsoidal uncertainty-set-based robust Capon beamformer (RCB) techniques in passive sonar. Regrettably, the computational complexity required to form RCB weights is cubic in the number of adaptive degrees of freedom, which is often prohibitive in practice. For this reason, several low-complexity techniques for computing RCB weights, or equivalent worst case robust adaptive beamformer weights, have recently been developed. These techniques, whose complexities are only quadratic in the number of adaptive degrees of freedom, use gradient-based, reduced-dimension Krylov-subspace or Kalman-filtering methods. In this work, we review these techniques for passive sonar, analyzing their complexities and evaluating them initially on simulated data. The best performing methods are then evaluated on two in-water recorded passive sonar data sets. One set, containing a strong controlled acoustic source, demonstrates the ability of the algorithms to protect against signal cancellation when pointing at the source, and their ability to reject the source when pointing away from it. The other data set, recorded during a period when the boat was accelerating, demonstrates the ability of the algorithms to operate in the presence of speed-induced noises.},
  author       = {Somasundaram, Samuel and Butt, Naveed and Jakobsson, Andreas and Hart, Les},
  issn         = {0364-9059},
  language     = {eng},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Journal of Oceanic Engineering},
  title        = {Low-Complexity Uncertainty-Set-Based Robust Adaptive Beamforming for Passive Sonar},
  url          = {http://dx.doi.org/10.1109/JOE.2015.2474495},
  year         = {2015},
}