Parallel algorithms for Robust Broadband MVDR beamforming

Priyabrata Sinha, Alan D. George, Keonwook Kim

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Rapid advancements in adaptive sonar beamforming algorithms have greatly increased the 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 significantly reduce execution time, power consumption and cost, and increase scalability and dependability. In this paper, the basic narrowband Minimum Variance Distortionless Response (MVDR) beamformer is enhanced by incorporating broadband processing, a technique to enhance the robustness of the algorithm, and speedup of the matrix inversion task using sequential regression. Using this Robust Broadband MVDR (RB-MVDR) algorithm as a sequential baseline, two novel parallel algorithms are developed and analyzed. Performance results are included, among them execution time, scaled speedup, parallel efficiency, result latency and memory utilization. The testbed used is a distributed system comprised of a cluster of personal computers connected by a conventional network.

Original languageEnglish
Pages (from-to)69-96
Number of pages28
JournalJournal of Computational Acoustics
Volume10
Issue number1
DOIs
StatePublished - 2002

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