Evidence map›Paper›PMID 35096049›Full record

ArticleComputational intelligence and neuroscience2022

A Neural Network-Based Method for Fast Capture and Tracking of Laser Links between Nonorbiting Platforms.

Bo Li, Siyuan Yu, Jing Ma, Liying Tan

RetractedAbstract readRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Bo LiNational Key Laboratory of Tunable Laser Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.ORCID https://orcid.org/0000-0002-4845-6651
Siyuan YuNational Key Laboratory of Tunable Laser Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.ORCID https://orcid.org/0000-0003-2568-6697
Jing MaNational Key Laboratory of Tunable Laser Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.ORCID https://orcid.org/0000-0002-9740-7370
Liying TanNational Key Laboratory of Tunable Laser Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.ORCID https://orcid.org/0000-0002-8645-8324

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, a neural network approach is used to conduct an in-depth study and analysis of the fast capture tracking method for laser links between nonorbiting platforms. The experimental platform of the convolutional neural network- (CNN-) based free-space optical communication (FSO) wavefront correction system is built indoors, and the wavefront distortion correction performance of the CNN-based wavefront correction method is investigated. The experimental results show that the coupling power loss can be reduced to small after the CNN method correction under weak and strong turbulence. The accuracy of the above model is verified by comparing the simulation data with the experimentally measured data, thus realizing the coordinate decoupling of the coarse aiming mechanism and weakening the influence of structural factors on the tracking accuracy of the system. The tracking correlation equation of the influence of beam far-field dynamic characteristics on the tracking stability of the link is established, and the correlation factor variance of beam far-field dynamic characteristics is used to provide a quantitative analysis method for the evaluation and prediction of the comprehensive performance of the link tracking stability. The influence of beam divergence angle, wavefront distortion, detector accuracy, and atmospheric turbulence disturbance on the correlation factor variance of beam far-field dynamic characteristics of laser link beacons is modelled, and the link tracking stability optimization method is proposed under the requirement of link tracking accuracy, which provides an effective solution analysis method to realize the improvement of laser link tracking stability.

Indexed as

LasersNeural Networks, ComputerComputer SimulationLight

Identifiers

PMID35096049
PMCPMC8799350

What OpenQuestion holds

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LicenceCC BY
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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.