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Technical Note
Peer-Review Record

Calibration of MIMO Radar Transmitting and Receiving Array Using Scene Object Measurement

Remote Sens. 2022, 14(15), 3573; https://doi.org/10.3390/rs14153573
by Łukasz Maślikowski
Reviewer 1:
Reviewer 3:
Remote Sens. 2022, 14(15), 3573; https://doi.org/10.3390/rs14153573
Submission received: 27 June 2022 / Revised: 20 July 2022 / Accepted: 21 July 2022 / Published: 25 July 2022
(This article belongs to the Special Issue Recent Advances in Signal Processing and Radar for Remote Sensing)

Round 1

Reviewer 1 Report

Dear author,

thank you for submitting this paper. The detailed comments are in the attached, annotated pdf file. My main comments are the following:

- I am missing a listing and comparison with other existing methods and also highlighting your contribution. Your paper compares a/an numerical/experimental investigation between your SVD approach and a non-calibrated system. Of course, the SVD approach should be better but how does it perform compared to other approaches?
- You list too few references for a paper of this length. You should add more to link it to other (current research).
- Revise the English text as well as the layout. You have partially bold text and/or wrong figures.
- You should extend the abstract and conclusion and describe it better. You should somehow support your statements quantitatively (i.e. numbers) and not only qualitatively.

Comments for author File: Comments.pdf

Author Response

Thank you for your meticulous work and time spent on assessment and improvement of my paper. Please find responses to all remarks in attached file.

Author Response File: Author Response.pdf

Reviewer 2 Report

1. The work under review is devoted to the calibration of MIMO radar transmitting and receiving array and is a continuation of the work of Maślikowski, Ł. Calibration of Transmitting and Receiving Array of a Radar using MIMO Measurement, 2021 Signal Processing Symposium (SPSympo), Łódź, Poland, 2021, pp. 189-192, doi: 10.1109/SPSympo51155.2020.9593475.

2. The author proposes two calibration methods based on statistical processing. To confirm their effectiveness, theoretical calculations and the result of the experiment are given.

3. However, the author points out that "The size of the array was determined by the available hardware limitations and is not big enough to prove the advantage of the proposed methods over simple normalization" (lines 235-237). If we analyze Fig. 14 and Fig. 15, it can be seen that when applying the methods proposed by the author, not only details that were previously absent appear, but also new ones appear that are not described in any way in the work.

4. Fig. 3 and 4 are the same, although they should describe different processes of normalization and averaging.

5. Fig. 5 is both a drawing and a formula. It is not clear why the desired value is written above the equal sign.

6. There are two Figs. 11 and no Fig. 12.

7. It is not clear for what purpose the author included in the text of the article instructions for the preparation of the list of references.

Author Response

Thank you for your work devoted to assessment and improvement of my paper. Please find responses to all remarks in attached file.

Author Response File: Author Response.pdf

Reviewer 3 Report

This is an interesting paper, with real experimental data. However, literature review part is quite weak. Contribution compared to what is currently known is not clearly justified.

Author Response

Thank you for your work devoted to assessment and improvement of my paper.

As the response to the remark,  the references have been expanded and commented in the first section. I hope that it shows novelty of the work a bit better.

Round 2

Reviewer 1 Report

Dear author,
thank you for taking my comments into account. The paper reads well and I can now see the benefits and advantages of the proposed methods.
Best regards

Reviewer 3 Report

Authors may add more discussion about why reference target based calibration is important or useful or advantageous compared to other techniques. 

Overall, this revised version does look much better.

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