PARALLEL ALGORITHMS FOR SPLIT-APERTURE CONVENTIONAL BEAMFORMING

Quiet submarine threats and high clutter in the littoral undersea environment increase the processing demands on beamforming arrays, particularly for applications which require in-array autonomous operation. Whereas traditional single-aperture beamforming approaches may falter, the Split-Aperture Conventional Beamforming (SA-CBF) algorithm can be used to meet stringent requirements for more precise bearing estimation. Moreover, by coupling each transducer node with a microprocessor, parallel processing of the split-aperture beamformer on a distributed system can glean advantages in execution speed, fault tolerance, scalability, and cost. In this paper, parallel algorithms for SA-CBF are introduced using coarse-grained and medium-grained forms of decomposition. Performance results from parallel and sequential algorithms are presented using a distributed system testbed comprised of a cluster of workstations connected by a high-speed network. The execution times, parallel efficiencies, and memory requirements of each parallel algorithm are presented and analyzed. The results of these analyses demonstrate that parallel in-array processing holds the potential to meet the needs of future advanced sonar beamforming algorithms in a scalable fashion.

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DISTRIBUTED PARALLEL PROCESSING TECHNIQUES FOR ADAPTIVE SONAR BEAMFORMING

Journal of Computational Acoustics ◽

10.1142/s0218396x02000511 ◽

2002 ◽

Vol 10 (01) ◽

pp. 1-23 ◽

Cited By ~ 9

Author(s):

ALAN D. GEORGE ◽

JESUS GARCIA ◽

KEONWOOK KIM ◽

PRIYABRATA SINHA

Keyword(s):

Parallel Processing ◽

Minimum Variance ◽

Adaptive Beamforming ◽

Autonomous Operation ◽

Minimum Variance Distortionless Response ◽

Efficiency And Effectiveness ◽

Execution Speed ◽

Processing Techniques ◽

Performance Results ◽

Communication Demands

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.

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PARALLEL SUBSPACE PROJECTION BEAMFORMING FOR AUTONOMOUS, PASSIVE SONAR SIGNAL PROCESSING

Journal of Computational Acoustics ◽

10.1142/s0218396x0300181x ◽

2003 ◽

Vol 11 (01) ◽

pp. 55-74

Author(s):

KEONWOOK KIM ◽

ALAN D. GEORGE

Keyword(s):

Signal Processing ◽

Distributed System ◽

Wide Band ◽

Subspace Projection ◽

Adaptive Beamformer ◽

Cluttered Environment ◽

Execution Speed ◽

Sonar Signal Processing ◽

Performance Results

Adaptive techniques can be applied to improve performance of a beamformer in a cluttered environment. The sequential implementation of an adaptive beamformer, for many sensors and over a wide band of frequencies, presents a serious computational challenge. By coupling each transducer node with a microprocessor, in-situ parallel processing applied to an adaptive beamformer on a distributed system can glean advantages in execution speed, fault tolerance, scalability, and cost. In this paper, parallel algorithms for Subspace Projection Beamforming (SPB), using QR decomposition on distributed systems, are introduced for in-situ signal processing. Performance results from parallel and sequential algorithms are presented using a distributed system testbed comprised of a cluster of computers connected by a network. The execution times, parallel efficiencies, and memory requirements of each parallel algorithm are presented and analyzed. The results of these analyses demonstrate that parallel in-situ processing holds the potential to meet the needs of future advanced beamforming algorithms in a scalable fashion.

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PARALLEL ALGORITHMS FOR ROBUST BROADBAND MVDR BEAMFORMING

Journal of Computational Acoustics ◽

10.1142/s0218396x02001565 ◽

2002 ◽

Vol 10 (01) ◽

pp. 69-96 ◽

Cited By ~ 14

Author(s):

PRIYABRATA SINHA ◽

ALAN D. GEORGE ◽

KEONWOOK KIM

Keyword(s):

Parallel Algorithms ◽

Execution Time ◽

Minimum Variance ◽

Autonomous Operation ◽

Minimum Variance Distortionless Response ◽

Distributed Array ◽

The Matrix ◽

Performance Results ◽

Communication Demands ◽

Sequential Regression

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.

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WebRTC - Realtime Communication for the Open Web Platform

Queue ◽

10.1145/3454122.3457587 ◽

2021 ◽

Vol 19 (1) ◽

pp. 77-93

Author(s):

Niklas Blum ◽

Serge Lachapelle ◽

Harald Alvestrand

Keyword(s):

High Speed ◽

Network Access ◽

The Past ◽

Human Contact ◽

High Speed Network ◽

The World ◽

Web Platform

In this time of pandemic, the world has turned to Internet-based, RTC (realtime communication) as never before. The number of RTC products has, over the past decade, exploded in large part because of cheaper high-speed network access and more powerful devices, but also because of an open, royalty-free platform called WebRTC. WebRTC is growing from enabling useful experiences to being essential in allowing billions to continue their work and education, and keep vital human contact during a pandemic. The opportunities and impact that lie ahead for WebRTC are intriguing indeed.

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