Evidence map›Paper›PMID 31861647›Full record

ArticleSensors (Basel, Switzerland)2019

A Novel Real-Valued DOA Algorithm Based on Eigenvalue.

De-Sen Yang, Feng Chen, Shi-Qi Mo

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Who cites it

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

3 authors.

De-Sen YangAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China.
Feng ChenCollege of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China.ORCID 0000-0003-3995-9211
Shi-Qi MoAcoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China.

Funding

he Program for Chang Jiang Scholars and Innovative Research Team in University of Ministry of Education of China No.IRT_16R17Submarine autonomous weapons platform in the deep sea No.KY10500180037
6 · The paper itself

Abstract

To solve the high complexity of the subspace-based direction-of-arrival (DOA) estimation algorithm, a super-resolution DOA algorithm is built in this paper. However, in this method, matrix decomposition is required for each search angle. Therefore, in this paper, real-valued processing is used to reduce the scanning range by half, which is less effective in algorithm complexity. The super-resolution algorithm mainly uses the conservation of energy. By exploring the relationship between the covariance matrix and its complex conjugate, we constructed the real-valued matrix and introduced a real-valued searching source to make the operation of the matrix real-valued. Finally, the simulation experiments show that the proposed algorithm not only reduces the spectral search range by half but also has a higher angular resolution than the traditional algorithm.

Indexed as

algorithm complexityDOAreal-valued processingsearch rangesuper-resolution

Identifiers

PMID31861647
PMCPMC6982889

What OpenQuestion holds

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Registered trials

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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.