Next Article in Journal
Usefulness of Potentially Probiotic L. lactis Isolates from Polish Fermented Cow Milk for the Production of Cottage Cheese
Next Article in Special Issue
Practical Performance Analysis of Interference in DSS System
Previous Article in Journal
Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
Previous Article in Special Issue
Car-Sense: Vehicle Occupant Legacy Hazard Detection Method Based on DFWS
 
 
Article
Peer-Review Record

mmSight: A Robust Millimeter-Wave Near-Field SAR Imaging Algorithm

Appl. Sci. 2022, 12(23), 12085; https://doi.org/10.3390/app122312085
by Zhanjun Hao 1,2,*, Ruidong Wang 1, Xiaochao Dang 1,2, Hao Yan 1 and Jianxiang Peng 1
Reviewer 1:
Reviewer 3:
Appl. Sci. 2022, 12(23), 12085; https://doi.org/10.3390/app122312085
Submission received: 29 October 2022 / Revised: 21 November 2022 / Accepted: 22 November 2022 / Published: 25 November 2022
(This article belongs to the Special Issue New Insights into Pervasive and Mobile Computing)

Round 1

Reviewer 1 Report

The authors report that the mmSight algorithm can image the common Fully-Sampled single target, hidden target, and multiple targets at the same distance, as well as solve the ghost image problem of a single target in the case of Sparsely-Sampled, and the projection problem of multiple targets at different distances, with an average reduction in Image Entropy of 0.3372. The work is very interesting and novel to be published in the prestigious Journal MDPI Applied Sciences in its present format.

Author Response

Please see the attachment 'reply1.pdf'.

Author Response File: Author Response.pdf

Reviewer 2 Report

Millimeter-wave SAR imaging is widely studied as a common means of RF imaging. Still, there are problems with the ghost image in Sparsely-Sampled cases and the projection of multiple targets at different distances. The paper proposes a robust imaging algorithm based on the Analytic Fourier Transform is proposed which is named mmSight.  The experimental results show that the proposed imaging algorithm in this paper, relative to other algorithms, can image common Fully-Sampled single target, hidden target, and multiple targets at the same distance, and solve the ghost image problem of a single target in the case of Sparsely-Sampled, as well as the projection problem of multiple targets at different distances; the Image Entropy of the mmSight is on average 0.3372 lower than that of other algorithms. 

 

 

Although the paper represents a contribution to the area of knowledge, it currently has some deficiencies that should be results, stories such as:

i) Self-contained abstract, the acronyms RF and ESR indicate which is the significance.

ii) In Page 2, lines 75-80: This is part of the conclusions.

iii) Improve the Keywords ( that were more representative of the paper)

iv) Justify how the results of table 3 were obtained.

vi) Add a discussion section on the results obtained.

vii) To Improve the conclusion.

 

Best Regards

Author Response

Thank you very much for your review. We have uploaded the pdf file to answer your questions. For more details, please see the revised manuscript.

Author Response File: Author Response.pdf

Reviewer 3 Report

More experimental result must be included. The process and detailed steps of experiments must be included. Conclusion part is not clear

Author Response

Thank you very much for your review. We have uploaded the pdf file to answer your questions. For more details, please see the revised manuscript.

Author Response File: Author Response.pdf

Reviewer 4 Report

After closely reviewing the entire article, I noticed various flaws. Before publishing, authors should think about the following points:

1-In the abstract and conclusion section, use absolute terms (numerical values) rather than relative values to support your findings.

2-The introduction section also lacks sufficient citations. The authors are suggested to use these five sources and cite them when discussing topics beyond this paper's scope.

https://www.mdpi.com/2076-3417/12/10/4848

https://www.sciencedirect.com/science/article/pii/S0010482522002530

https://www.sciencedirect.com/science/article/abs/pii/S2210670722004061

https://www.sciencedirect.com/science/article/pii/S0010482521009355

https://ieeexplore.ieee.org/abstract/document/9721538

3-Sort works in chronological order first in the related work section, then add a related work table. Finally, in the related work table, include your work to demonstrate its own novelty.

4-Add extra information to the captions of Figs 1 and 2.

5-If formulas are borrowed from other works, they must be cited.

6-The discussion and future works must be expanded ( More Figs and Tables are needed)

7-The implications of the work beyond the scope must be stated in the conclusion section.

Author Response

Thank you very much for your review. We have uploaded the pdf file to answer your questions. For more details, please see the revised manuscript.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The current version of the paper presents improvements to the article to be included in this journal. There are some points to improve:

 

i) To describe in general terms the algorithm presented: Algorithm 1

ii) To review the grammar and connection between paragraphs.

iii) To explain and reference equation 16 (page 17)  from a scientific article.

 

Best regards

Author Response

Thank you very much for your suggestions on our work! Our reply is in the PDF file, and the changes are in the additional materials.

Author Response File: Author Response.pdf

Reviewer 3 Report

Introduction part may be improved. More case study must be included on support of novelty. Quality of presentation may be improved 

Author Response

Thank you very much for your suggestions on our work! Our reply is in the PDF file, and the changes are in the additional materials.

Author Response File: Author Response.pdf

Reviewer 4 Report

Now, it can be accepted.

Author Response

We are very grateful for your appreciation and recognition of our work!

Back to TopTop