Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing.

Zhibo Shi, Guolong Liang, Longhao Qiu, Guangming Wan, Lei Zhao

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhibo ShiAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China.ORCID 0000-0001-5478-7038

Guolong LiangAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China.

Longhao QiuAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China.

Guangming WanAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China.

Lei ZhaoAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China.

Funding

National Defense Basic Scientific Research Program of China JCKY2019604B001Provincial Funding Projects of National Key R&D Program of China GX18C019the National Key R&D Program of China 2016YFC1400101

6 · The paper itself

Abstract

Array design is the primary consideration for array signal processing, and sparse array design is an important and challenging task. In underwater acoustic environments, the vector hydrophone array contains more information than the scalar hydrophone array, but there are few articles focused on the design of the vector hydrophone array. The difference between the vector hydrophone array and the scalar hydrophone array is that each vector hydrophone has three or four channels. When designing a sparse vector hydrophone array, these channels need to be optimized at the same time to ensure the sparsity of the array elements' number. To solve this problem, this paper introduced the compressed sensing (CS) theory into the vector hydrophone array design, constructed the vector hydrophone array design problem into a globally solvable optimization problem, proposed a CS-based algorithm with the L

Indexed as

array designbeam patterncompressed sensingoff-grid

Identifiers

PMID33291843

DOI10.3390/s20236949

PMCPMC7731401

What OpenQuestion holds

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.