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Ting Jiang
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ORCiD: https://orcid.org/0000-0003-3598-3804
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In this paper, the influence of seasonal variation on target detection accuracy and the effectiveness of deep factor analysis(DFA) in signal denoising are studied. To extensively verify the universality of the DFA_based approach, a variety of target objects, including no target, human, wood board and iron cabinet targets, are measured in foliage environment under four different weather conditions. Then, after removing background noise from the collected data, deep factor analysis is carried out to reduce the impact of noise. The experimental results show that the influence of weather variation on target detection can be effectively eliminated by DFA_based algorithm, which can improve the average classification accuracy in all seasons. Finally, by means of cross validation, the effectiveness of DFA_based algorithm on signal denoising and the influence on target detection accuracy are further studied. The method is stable and universal in any weather conditions, even in foggy and snowy days, which can be stable at about 93%.
Keywords
impulse-radio ultra-wideband(IR-UWB), Deep factor analysis, Target detection
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CURRENT STATUS: Published
View the published article at EURASIP Journal on Wireless Communications and Networking.
Version 3
Posted 12 Feb, 2021
No community comments so far
Editorial decision: Accept
On 03 Feb, 2021
Editor assigned
On 02 Feb, 2021
Reviewers invited
Invitations sent on 02 Feb, 2021
Reviewer #1 agreed
On 02 Feb, 2021
Review #1 received
Received 02 Feb, 2021
Submission checks complete
On 02 Feb, 2021
Editor invited
On 02 Feb, 2021
No comments provided
Editorial decision: Minor revision
On 05 Jan, 2021
Review #2 received
Received 07 Dec, 2020
Reviewer #2 agreed
On 25 Nov, 2020
Review #1 received
Received 19 Sep, 2020
Reviewer #1 agreed
On 04 Sep, 2020
Reviewers invited
Invitations sent on 01 Sep, 2020
Editor assigned
On 27 Aug, 2020
Submission checks complete
On 26 Aug, 2020
Editor invited
On 26 Aug, 2020
No comments provided
Editorial decision: Major revision
On 19 Jul, 2020
Review #3 received
Received 18 Jul, 2020
Reviewer #3 agreed
On 15 Jul, 2020
Review #1 received
Received 25 May, 2020
Review #2 received
Received 25 May, 2020
Reviewers invited
Invitations sent on 07 May, 2020
Reviewer #1 agreed
On 07 May, 2020
Reviewer #2 agreed
On 07 May, 2020
Editor assigned
On 13 Apr, 2020
Editor invited
On 12 Apr, 2020
Submission checks complete
On 26 Mar, 2020
First submitted
On 22 Mar, 2020
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A new preprint design is coming!
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See the published version of this preprint at EURASIP Journal on Wireless Communications and Networking.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Ting Jiang
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3598-3804
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at EURASIP Journal on Wireless Communications and Networking.
Version 3
Posted 12 Feb, 2021
No community comments so far
Editorial decision: Accept
On 03 Feb, 2021
Editor assigned
On 02 Feb, 2021
Reviewers invited
Invitations sent on 02 Feb, 2021
Reviewer #1 agreed
On 02 Feb, 2021
Review #1 received
Received 02 Feb, 2021
Submission checks complete
On 02 Feb, 2021
Editor invited
On 02 Feb, 2021
No comments provided
Editorial decision: Minor revision
On 05 Jan, 2021
Review #2 received
Received 07 Dec, 2020
Reviewer #2 agreed
On 25 Nov, 2020
Review #1 received
Received 19 Sep, 2020
Reviewer #1 agreed
On 04 Sep, 2020
Reviewers invited
Invitations sent on 01 Sep, 2020
Editor assigned
On 27 Aug, 2020
Submission checks complete
On 26 Aug, 2020
Editor invited
On 26 Aug, 2020
No comments provided
Editorial decision: Major revision
On 19 Jul, 2020
Review #3 received
Received 18 Jul, 2020
Reviewer #3 agreed
On 15 Jul, 2020
Review #1 received
Received 25 May, 2020
Review #2 received
Received 25 May, 2020
Reviewers invited
Invitations sent on 07 May, 2020
Reviewer #1 agreed
On 07 May, 2020
Reviewer #2 agreed
On 07 May, 2020
Editor assigned
On 13 Apr, 2020
Editor invited
On 12 Apr, 2020
Submission checks complete
On 26 Mar, 2020
First submitted
On 22 Mar, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Systems and Networking
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at EURASIP Journal on Wireless Communications and Networking.
In this paper, the influence of seasonal variation on target detection accuracy and the effectiveness of deep factor analysis(DFA) in signal denoising are studied. To extensively verify the universality of the DFA_based approach, a variety of target objects, including no target, human, wood board and iron cabinet targets, are measured in foliage environment under four different weather conditions. Then, after removing background noise from the collected data, deep factor analysis is carried out to reduce the impact of noise. The experimental results show that the influence of weather variation on target detection can be effectively eliminated by DFA_based algorithm, which can improve the average classification accuracy in all seasons. Finally, by means of cross validation, the effectiveness of DFA_based algorithm on signal denoising and the influence on target detection accuracy are further studied. The method is stable and universal in any weather conditions, even in foggy and snowy days, which can be stable at about 93%.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
The full text of this article is available to read as a PDF.
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