Distributed parallel processing techniques for adaptive sonar beamforming

Alan D. George, Jesus Garcia, Keonwook Kim, Priyabrata Sinha

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Quiet submarine threats and high clutter in the littoral environment increase computation and communication demands on beamforming arrays, particularly for applications that require in-array autonomous operation. By coupling each transducer node in a distributed array with a microprocessor, and networking them together, embedded parallel processing for adaptive beamformers can glean advantages in execution speed, fault tolerance, scalability, power, and cost. In this paper, a novel set of techniques for the parallelization of adaptive beamforming algorithms is introduced for in-array sonar signal processing. A narrowband, unconstrained, Minimum Variance Distortionless Response (MVDR) beamformer is used as a baseline to investigate the efficiency and effectiveness of this method in an experimental fashion. Performance results are also included, among them execution times, parallel efficiencies, and memory requirements, using a distributed system testbed comprised of a cluster of workstations connected by a conventional network.

Original languageEnglish
Pages (from-to)1-23
Number of pages23
JournalJournal of Computational Acoustics
Volume10
Issue number1
DOIs
StatePublished - 2002

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