Conference proceeding
Tracking the sparseness of the underlying support in shallow water acoustic communications
Proceedings of SPIE, Vol.8365(1), pp.83650N-83650N-7
Compressive Sensing
06/08/2012
DOI: 10.1117/12.921073
Abstract
Tracking the shallow water acoustic channel in real time poses an open challenge towards improving the data rate
in high-speed underwater communications. Multipath arrivals due to reflection from the moving ocean surface
and the sea bottom, along with surface wave focusing events, lead to a rapidly fluctuating complex-valued channel
impulse response and associated Delay-Doppler spread function that follow heavy-tailed distributions. The sparse
channel or Delay-Doppler spread function components are difficult to track in real time using popular sparse
sensing techniques due to the coherent and dynamic nature of the optimization problem as well as the timevarying
and potentially non-stationary sparseness of the underlying support. We build on related work using
non-convex optimization to track the shallow water acoustic channel in real time at high precision and tracking
speed to develop strategies to estimate the non-stationary sparseness of the underlying support. Specifically, we
employ non-convex manifold navigational techniques to estimate the support sparseness to balance the weighting
between the L1 norm of the tracked coefficients and the L2 norm of the estimation error. We explore the efficacy
of our methods against experimental field data collected at 200 meters range, 15 meters depth and varying wind
conditions.
Details
- Title: Subtitle
- Tracking the sparseness of the underlying support in shallow water acoustic communications
- Creators
- Ananya Sen Gupta - Woods Hole Oceanographic InstitutionJames Preisig - Woods Hole Oceanographic Institution
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.8365(1), pp.83650N-83650N-7
- Conference
- Compressive Sensing
- DOI
- 10.1117/12.921073
- ISSN
- 0277-786X
- Language
- English
- Date published
- 06/08/2012
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197459502771
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