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Research Article
Chengbo Xue
Beijing Institute of Technology
Corresponding Author
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The sum-difference coarray is the union of difference coarray and the sum coarray, which is capable to obtain a higher number of degrees of freedom (DOF) than the difference coarray. However, this method fails to use all information provided by the coprime array because of the existence of holes. In this paper, we introduce the virtual array interpolation into the sum-difference coarray domain. After interpolating the virtual array, we estimate the DOA by reconstructing the covariance matrix to resolve an atomic norm minimization problem in a gridless way. The proposed method is gridless and can effectively utilize the DOF of a larger virtual array. Numerical simulation results verify the effectiveness and the superior performance of the proposed algorithm.
Keywords
sum-difference coarray, virtual array interpolation, atomic norm, gridless Toeplitz matrix reconstruction
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CURRENT STATUS: Published
View the published article at EURASIP Journal on Advances in Signal Processing.
Version 1
Posted 11 May, 2021
No community comments so far
Editorial decision: Minor revision
On 01 Jun, 2021
Review #1 received
Received 31 May, 2021
Review #2 received
Received 30 May, 2021
Reviews received
Received 10 May, 2021
Reviewer #2 agreed
On 10 May, 2021
Reviewer #1 agreed
On 10 May, 2021
Reviewers invited
Invitations sent on 06 May, 2021
Submission checks complete
On 06 May, 2021
Editor assigned
On 05 May, 2021
Editor invited
On 05 May, 2021
First submitted
On 25 Apr, 2021
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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 Advances in Signal Processing.
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 Article
Chengbo Xue
Beijing Institute of Technology
Corresponding Author
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 Advances in Signal Processing.
Version 1
Posted 11 May, 2021
No community comments so far
Editorial decision: Minor revision
On 01 Jun, 2021
Review #1 received
Received 31 May, 2021
Review #2 received
Received 30 May, 2021
Reviews received
Received 10 May, 2021
Reviewer #2 agreed
On 10 May, 2021
Reviewer #1 agreed
On 10 May, 2021
Reviewers invited
Invitations sent on 06 May, 2021
Submission checks complete
On 06 May, 2021
Editor assigned
On 05 May, 2021
Editor invited
On 05 May, 2021
First submitted
On 25 Apr, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at EURASIP Journal on Advances in Signal Processing.
The sum-difference coarray is the union of difference coarray and the sum coarray, which is capable to obtain a higher number of degrees of freedom (DOF) than the difference coarray. However, this method fails to use all information provided by the coprime array because of the existence of holes. In this paper, we introduce the virtual array interpolation into the sum-difference coarray domain. After interpolating the virtual array, we estimate the DOA by reconstructing the covariance matrix to resolve an atomic norm minimization problem in a gridless way. The proposed method is gridless and can effectively utilize the DOF of a larger virtual array. Numerical simulation results verify the effectiveness and the superior performance of the proposed algorithm.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
The full text of this article is available to read as a PDF.
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