UAV Swarm Target Identification and Quantification Based on Radar Signal Independency Characterization
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper presents a new swarm target identification and quantification method based on complex valued independent component analysis (cICA) for the narrowband radar framework. The proposed method first determines detection thresholds from shape parameters of clutter signals decomposed by cICA, then performs UAV quantification procedure based on continuous target detections, and finally applies K-means clustering method to estimation swarm unit numbers. The proposed method is verified with various multimodality UAV swarm flight plans using a dynamic UAV radar signal simulation platform. I have the following comments:
1. In Figure 1, the symbol “Z” should be changed to symbol “Y” in “Whitening” and “Blind Source Separation”, and the equation in the last box should be revised to equation (13). The description of equations in the figure should be consistent with those in the previous text.
2. Figures 2,3 and 6 are not clear and need to be redrawn.
3. In Figure 7, the number of UAVs does not match the previous description.
Author Response
This paper presents a new swarm target identification and quantification method based on complex valued independent component analysis (cICA) for the narrowband radar framework. The proposed method first determines detection thresholds from shape parameters of clutter signals decomposed by cICA, then performs UAV quantification procedure based on continuous target detections, and finally applies K-means clustering method to estimation swarm unit numbers. The proposed method is verified with various multimodality UAV swarm flight plans using a dynamic UAV radar signal simulation platform. I have the following comments:
Comment-1: In Figure 1, the symbol “Z” should be changed to symbol “Y” in “Whitening” and “Blind Source Separation”, and the equation in the last box should be revised to equation (13). The description of equations in the figure should be consistent with those in the previous text.
Response: We apologize for this mistake. We have revised mathematical formulations during the paper composition, but forgot to update the figure. Figure 1 is revised according to reviewer’s comments and some other types are also corrected. We deeply appreciate reviewer’s careful reading. Thank you very much!
Comment-2: Figures 2,3 and 6 are not clear and need to be redrawn.
Response: All figures in the manuscript are reproduced to elevate their clarity. Thank you very much!
Comment-3: In Figure 7, the number of UAVs does not match the previous description.
Response: We apologize for this mistake. Contents related to Figure 7 are revised. We deeply appreciate reviewer’s careful reading.
Reviewer 2 Report
Comments and Suggestions for AuthorsThis paper proposes a radar signal processing framework based on complex valued independent component analysis (cICA) for swarm target identification and quantification. The article is innovative and some problems should be checked by authors.
1.The Introduction is too complicated, and it should be more brief and logical. Additionally, the current problems and the main contributions of this paper should be emphasized.
2. The figures need to be redrawn so that the text needs to be clear in the figures and the font should be further enlarged.
3. Please further explain the limitations of the proposed signal processing framework, and the contributions of the paper should be highlighted explicitly.
4. Please revise the language of the article to make the expression more concise.
5. Please further explain the reason why the performance of the ICA is better than CA-CFAR and OS-CFAR.
6. The real-time performance and complexity of the algorithms should be discussed.
Comments on the Quality of English Languagesee Comments and Suggestions for Authors
Author Response
This paper proposes a radar signal processing framework based on complex valued independent component analysis (cICA) for swarm target identification and quantification. The article is innovative and some problems should be checked by authors.
Comment-1: The Introduction is too complicated, and it should be more brief and logical. Additionally, the current problems and the main contributions of this paper should be emphasized.
Response: We went through the introduction section, and found its organization is messy with an ambiguous logic. Therefore, we made major revisions in the introduction part. We deeply appreciate reviewer’s constructive comments. Thank you very much!
Comment-2: The figures need to be redrawn so that the text needs to be clear in the figures and the font should be further enlarged.
Response: We reproduced all figures in the manuscript and elevate clarity. Thank you very much!
Comment-3: Please further explain the limitations of the proposed signal processing framework, and the contributions of the paper should be highlighted explicitly.
Response: We complement specific discussions about limitations of the proposed method in the last part of section 4. We deeply appreciate reviewer’ constructive comments. Thank you very much!
Comment-4: Please revise the language of the article to make the expression more concise.
Response: We have gone through the entire manuscript and revised expressions more concisely. Some typos are also corrected. We deeply appreciate reviewer’s constructive comments. Thank you very much!
Comment-5: Please further explain the reason why the performance of the ICA is better than CA-CFAR and OS-CFAR.
Response: This is a good suggestion and we deeply appreciate it. We indeed find out that we did not give explanations about why ICA-based method is better than conventional detection methods. We complement this in the last part of section 3.2.2. Thank you very much for your careful reading and these constructive comments!
Comment-6: The real-time performance and complexity of the algorithms should be discussed.
Response: We added more discussions about numerical complexity of cICA. This gives more consolidated support to explain the efficiency bottleneck of the proposed method. We deeply appreciate reviewer’s constructive comments.
Reviewer 3 Report
Comments and Suggestions for AuthorsThis article proposes a UAV swarm target identification method. But I have the following concerns.
1. The comparative experiments are not sufficient, and the author should increase the comparison with advanced methods instead of traditional CFAR methods.
2. The author should also expand the introduction section to discuss more advanced methods, such as those based on deep learning.
Comments on the Quality of English LanguageModerate editing of English language required.
Author Response
This article proposes a UAV swarm target identification method. But I have the following concerns.
Comment-1: The comparative experiments are not sufficient, and the author should increase the comparison with advanced methods instead of traditional CFAR methods.
Response: We agree with reviewer’s concerns. We also realize that the simple comparison with conventional CFAR detection methods is insufficient to validate the proposed method. We take reviewer’s constructive suggestion and select a representative target detection method using advanced radar signal processing method. The method is reproduced and results are compared with existing methods. Relative contents are added into section 3 and corresponding figures are also updated. We deeply appreciate reviewer’s constructive comments to improve our manuscript. Thank you very much!
Comment-2: The author should also expand the introduction section to discuss more advanced methods, such as those based on deep learning.
Response: We have gone through the introduction section according to reviewers’ comments, and find contents and organizations of the introduction are messy and ambiguous. Therefore, we reorganized the introduction section to clarify the logic. Reviewer’s suggestions about adding more discussions about advanced methods are also taken. The revised introduction is more comprehensive with a more clarified logic. We deeply appreciate reviewer’s constructive suggestions to improve the manuscript. Thank you very much!
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsNo further comments.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe manuscript can be accepted
