Review Reports

Round 1

Reviewer 1 Report

Please see the attached PDF file.

 

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

This paper focuses on the problem of parameter estimation of two-parameter distribution and carries out theoretical derivation and test data verification. Through the derivation of the relationship between the k-order origin moment and its derivative, a parameter estimation method based on single-order numerical solution is proposed, and the performance of the proposed algorithm is analyzed by simulation data and test data respectively. This paper is rigorous in derivation, standard in writing, and innovative to a certain extent. A few questions are briefly raised for the author's reference, as follows:

1))The authors don’t clearly point out the main defects of the existing works and mention the motivation of this work in the Introduction. Please rewrite the related paragraphs.

2) Please explain the relationship between the proposed method and the classical zlogz algorithm for parameter estimation of K distribution.

3) The calculation time of the proposed method is not optimal. Why？

4)The simulation section should provide more details of parameter setting.

5) Some grammar mistakes need to be corrected.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

In this paper, by calculating the relationship between the k-order origin moment and its derivative, a parameter estimation method based on the origin moment derivative is proposed. The estimation efficiency and accuracy are compared with some moment estimation methods. I have some questions as follows:

1.     In line 83, what’s the meaning of each symbol of equation (1)? Please clarify.

2.     In your simulation experiment, please add some figures to illustrate the K-distribution you performed. In this case, readers may have a better understanding of your simulation experiment.

3.     In the measured data experiment, please add some references about the Data when you refer to the Data in the paper.

4.     In the measured data experiment, please add some introduction of the Data. Readers may not be familiar with the Data you used.

5.     In the measured data experiment. Please add some figures to illustrate the data.

6.     In addition, how to evaluate the accuracy of the proposed method in the measured data experiment since the true value is unknown？

 

7.     In the abstract, I disagree with the statement “Both simulation data and measured clutter data show that this method can achieve 100% estimation efficiency and can obtain higher estimation accuracy”. How can it achieve 100% estimation efficiency?

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Please see the attached pdf file.

Comments for author File: Comments.pdf

Reviewer 3 Report

Thanks for the author's response.  All my questions have been addressed. The paper can be accepted after minor revisions.

In  Table 1, The first letter should be capitalized.