Paper
8 June 2012 Tracking the sparseness of the underlying support in shallow water acoustic communications
Ananya Sen Gupta, James Preisig
Author Affiliations +
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ananya Sen Gupta and James Preisig "Tracking the sparseness of the underlying support in shallow water acoustic communications", Proc. SPIE 8365, Compressive Sensing, 83650N (8 June 2012); https://doi.org/10.1117/12.921073
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KEYWORDS
Acoustics

Water

Data modeling

Detection and tracking algorithms

Error analysis

Receivers

Chemical elements

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