A Fast Facet-Based SAR Imaging Model and Target Detection Based on YOLOv5 with CBAM and Another Detection Head

Round 1

Reviewer 1 Report

A facet-based SAR image model and target detection based on improved YOLOv5" presents a novel approach for SAR image target detection by proposing a facet-based SAR imaging model and utilizing an improved YOLOv5 network. The authors have also established a dataset of SAR images for two typical military targets. The paper provides a comprehensive analysis of electromagnetic scattering, discusses the iterative physical optics method, and introduces the fast far-field approximation technique. The proposed method is evaluated through simulation results, and the practical application in situational awareness of battlefield conditions is highlighted.

The paper addresses an important problem in the field of synthetic aperture radar (SAR) image target detection and presents a novel solution. However, there are some areas that require improvement and clarification. I have outlined the major comments and suggestions below:

1.       The abstract provides a general overview of the paper, but it lacks specific details about the proposed approach and the key findings. It would be helpful to include more specific information about the facet-based SAR imaging model, the improved YOLOv5 network, and the results obtained.

2.       The introduction provides a good background and motivation for the research. However, it would be beneficial to include a clear statement of the research objectives or research questions that the paper aims to address. What are the specific goals of this study?

3.       The authors mention that a dataset including SAR images of two typical military targets is established. However, there is no further explanation or description of this dataset. It would be valuable to provide more details about the dataset, such as the size of the dataset, the acquisition process, and any preprocessing steps applied.

4.       The paper briefly mentions the facet-based SAR imaging model and the improved YOLOv5 network, but lacks sufficient details about these methods. It is crucial to provide a clear and comprehensive description of the proposed methods, including the underlying principles and any modifications or improvements made. This would help readers understand the novelty and technical contributions of the paper.

5.       The paper mentions that simulation results show the effectiveness of the proposed algorithm. However, no specific details or quantitative results are presented in this section. It is important to include a detailed analysis of the simulation results, including performance metrics, comparisons with existing methods, and discussions of the achieved performance.

6.       The paper mentions the practical application of the proposed simulation system in situational awareness of battlefield conditions. However, it would be helpful to elaborate on this application and provide examples or scenarios where the proposed system can be deployed effectively.

7.       The structure and organization of the paper need improvement. The paper jumps between different topics and lacks a clear flow of ideas. It is recommended to revise the organization of the paper to ensure a logical progression of the content, with clear subsections for each major topic.

8.       The paper needs significant improvements in terms of language and clarity. The writing style is often convoluted, making it difficult to understand the intended meaning. There are also several grammatical errors and inconsistencies throughout the text. I recommend thorough proofreading and revision to improve the overall clarity and readability of the paper.

9.       The paper includes Figure 1, which illustrates the geometry of typical targets. However, the figure lacks labels and descriptions, making it difficult to understand the specific details being presented. It is important to provide clear and informative captions for all figures, describing the content and purpose of each figure.

10.   Highlight the key contributions and outcomes of the research, emphasizing their significance in the civilian and military fields.

11.   Acknowledge the limitations or shortcomings of the present study. Be specific about any constraints or challenges faced during the research process. This demonstrates a realistic perspective and opens up opportunities for future improvement.

12.   Provide suggestions for future research and improvements based on the identified limitations. For example, mention the need for a fast facet-based SAR imaging algorithm to enhance real-time imaging. Encourage further investigation in specific areas that can address the identified shortcomings.

13.   Briefly discuss the effectiveness of the employed methodology, such as the iterative physical optics and Kirchhoff approximation algorithm, and the facet-based SAR image simulation method. Comment on how these methods contributed to the overall results and offer insights into their potential applications or improvements.

A facet-based SAR image model and target detection based on improved YOLOv5" presents a novel approach for SAR image target detection by proposing a facet-based SAR imaging model and utilizing an improved YOLOv5 network. The authors have also established a dataset of SAR images for two typical military targets. The paper provides a comprehensive analysis of electromagnetic scattering, discusses the iterative physical optics method, and introduces the fast far-field approximation technique. The proposed method is evaluated through simulation results, and the practical application in situational awareness of battlefield conditions is highlighted.

The paper addresses an important problem in the field of synthetic aperture radar (SAR) image target detection and presents a novel solution. However, there are some areas that require improvement and clarification. I have outlined the major comments and suggestions below:

1.       The abstract provides a general overview of the paper, but it lacks specific details about the proposed approach and the key findings. It would be helpful to include more specific information about the facet-based SAR imaging model, the improved YOLOv5 network, and the results obtained.

2.       The introduction provides a good background and motivation for the research. However, it would be beneficial to include a clear statement of the research objectives or research questions that the paper aims to address. What are the specific goals of this study?

3.       The authors mention that a dataset including SAR images of two typical military targets is established. However, there is no further explanation or description of this dataset. It would be valuable to provide more details about the dataset, such as the size of the dataset, the acquisition process, and any preprocessing steps applied.

4.       The paper briefly mentions the facet-based SAR imaging model and the improved YOLOv5 network, but lacks sufficient details about these methods. It is crucial to provide a clear and comprehensive description of the proposed methods, including the underlying principles and any modifications or improvements made. This would help readers understand the novelty and technical contributions of the paper.

5.       The paper mentions that simulation results show the effectiveness of the proposed algorithm. However, no specific details or quantitative results are presented in this section. It is important to include a detailed analysis of the simulation results, including performance metrics, comparisons with existing methods, and discussions of the achieved performance.

6.       The paper mentions the practical application of the proposed simulation system in situational awareness of battlefield conditions. However, it would be helpful to elaborate on this application and provide examples or scenarios where the proposed system can be deployed effectively.

7.       The structure and organization of the paper need improvement. The paper jumps between different topics and lacks a clear flow of ideas. It is recommended to revise the organization of the paper to ensure a logical progression of the content, with clear subsections for each major topic.

8.       The paper needs significant improvements in terms of language and clarity. The writing style is often convoluted, making it difficult to understand the intended meaning. There are also several grammatical errors and inconsistencies throughout the text. I recommend thorough proofreading and revision to improve the overall clarity and readability of the paper.

9.       The paper includes Figure 1, which illustrates the geometry of typical targets. However, the figure lacks labels and descriptions, making it difficult to understand the specific details being presented. It is important to provide clear and informative captions for all figures, describing the content and purpose of each figure.

10.   Highlight the key contributions and outcomes of the research, emphasizing their significance in the civilian and military fields.

11.   Acknowledge the limitations or shortcomings of the present study. Be specific about any constraints or challenges faced during the research process. This demonstrates a realistic perspective and opens up opportunities for future improvement.

12.   Provide suggestions for future research and improvements based on the identified limitations. For example, mention the need for a fast facet-based SAR imaging algorithm to enhance real-time imaging. Encourage further investigation in specific areas that can address the identified shortcomings.

13.   Briefly discuss the effectiveness of the employed methodology, such as the iterative physical optics and Kirchhoff approximation algorithm, and the facet-based SAR image simulation method. Comment on how these methods contributed to the overall results and offer insights into their potential applications or improvements.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Strength:

1. The writing is easy to follow. 

2. The method is straightforward, and the authors' changes to Yolo to improve its performance make sense. 

3. the results show significant improvement compared to standard yolo. 

Weakness:

1. How is the facet-based SAR image model evaluated? since this is one of the major contributions of this model, it would be needed to to quantify the performance.

1. The novelty of the methodology is limited, attention module and multi-feature extraction and fusion is popular methodologies for small object detection. 

2. The experiment compares the results with the base Yolo model, but it would be more convincing to compare against other small object detection methodologies.

3. In 3.2.1. the author mentioned edge detection, but how is it used for small object detection? how is it used in the method? how much impact it has on the final results is not clear. 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Dear authors,

After reviewing this paper, I have made an effort to understand the content. It appears that the manuscript utilizes a facet-based scattering model, Kirchhoff approximation, and SAR imaging characteristics to simulate SAR images for ultra-low altitude targets, specifically fighter jets and missiles. The authors also propose an improved YOLO network model by incorporating an adaptive and robust edge detection detector and a convolutional Block attention module. The performance and effectiveness of the proposed model are discussed using simulation data. The authors have conducted solid work; however, the structure of the manuscript feels somewhat confusing. One concern is the level of innovation presented in this paper compared to the current state of research. As far as I know, facet-based scattering models and the YOLO network are already widely used in SAR image simulation and target detection. It would be beneficial if the authors could highlight their specific contributions and explain why their strategies were prioritized. With that in mind, I have provided the following comments to help enhance the quality of this manuscript:

Comments:

1. The title is too vague to reflect your innovation. It would be better to consider highlighting your true contribution. As the facet-based SAR image model is already widely used, the term "improved xxx" is not specific enough to establish trust.

2. Please rewrite your abstract.

3. In the introduction, the flow of the content is difficult to follow. Please consider introducing your research in the following manner: background, research problem, current works, research gap, and your efforts. Additionally, I could not find an explanation of what "EM" refers to.

4. To validate the reliability of your simulated data, is there any actual availability data that can be used for comparison? Relying solely on the simulated data generated by your model makes it challenging to support your conclusion that you have solved the problem of the lack of SAR datasets for typical military targets.

5. Regarding the detection model, please provide more detailed information about your innovations, such as the adaptive and robust edge detection detector and the convolutional Block attention module.

6. All the simulated SAR images appear too dark to be observed clearly. You may need to normalize them using linear or logarithmic methods.

7. Your conclusion is too simple. Please reorganize it to include the following elements:

• Overview of what this work was about.
• Main results and contributions.
• Comments on the importance.
• Tips for practical use, explaining how your results or experience can help someone in
practice or another researcher in using your simulator or avoiding pitfalls.
• Future work, reinforcing the importance of your work while avoiding giving away your ideas.

I hope these comments will help improve the quality of your manuscript

Dear authors,

Even though I am not qualified to comment on the language, I would say the language expression of this paper need to be improved, especially the logic of expression, and the authors need to learn more about how to write a scientific paper, like the abstract, introduction and conclusion.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thanks for addressing the concerns. I have no more coments

Reviewer 3 Report

Dear Authors,

Thank you for your efforts to give a revision. I have no more comments.