Modeling Small UAV Micro-Doppler Signature Using Millimeter-Wave FMCW Radar
Round 1
Reviewer 1 Report
This paper presents a Modeling Small UAVs Micro Doppler Signature by4 Millimeter Wave FMCW Radar. The work is interesting but some revisions are needed to accept this manuscript as a Journal paper. Comments to improve the manuscript are as follows;
- The application of the project related to detect and classify small-type UAV under the conditions of slow-flying speeds, and low flying altitudes. Some researchers have focus on the same problem using the ceiling cameras or fixing specific objects on the ground. For example, Speed-up Automatic Quadcopter Position Detection by Sensing Propeller Rotation, A Study on Hovering Control of Small Aerial Robot by Sensing Existing Floor Features, Development of an Automated Camera-Based Drone Landing System. Recommend Authors to discuss in the introduction, mentioning the de-merits of these camera based methods and merits of the Millimeter Wave FMCW Radar based methods.
- Theory part of the manuscript and authors introduced model is well-presented. I wonder that the term "Engine" miss-lead the readers. Better to use "Thrust of motor" or any other alternative term.
- In the experiments, pls mention the experimental environment in more details adding the physical relationship(distance) between Radar and the Drone propeller/s.
- In the experiments, authors just show the data analysis of the proposed model. I recommend authors to show some measurements data of drone speed or drone altitude using the proposal. This will improve the quality of the manuscript.
Author Response
Comments and Suggestions for Authors
This paper presents a Modeling Small UAVs Micro Doppler Signature by4 Millimeter Wave FMCW Radar. The work is interesting but some revisions are needed to accept this manuscript as a Journal paper. Comments to improve the manuscript are as follows;
- The application of the project related to detect and classify small-type UAV under the conditions of slow-flying speeds, and low flying altitudes. Some researchers have a focus on the same problem using the ceiling cameras or fixing specific objects on the ground. For example, Speed-up Automatic Quadcopter Position Detection by Sensing Propeller Rotation, A Study on Hovering Control of Small Aerial Robot by Sensing Existing Floor Features, Development of an Automated Camera-Based Drone Landing System. Recommend Authors to discuss in the introduction, mentioning the de-merits of these camera-based methods and merits of the Millimeter Wave FMCW Radar-based methods.
The introduction of the revised manuscript contains comments related to the use of optical and acoustic technologies, with associated references, along with motivation of their potential weakness in adverse meteorological and environmental conditions.
- Theory part of the manuscript and authors introduced model is well-presented. I wonder that the term "Engine" miss-lead the readers. Better to use "Thrust of motor" or any other alternative term.
We followed your suggestion. We replaced “engine” word with “motor”, as we also think it is clearer for the reader.
- In the experiments, pls mention the experimental environment in more details adding the physical relationship(distance) between Radar and the Drone propeller/s.
We improved description of anechoic chamber adding useful details to clarify experimental scenario.
- In the experiments, authors just show the data analysis of the proposed model. I recommend authors to show some measurements data of drone speed or drone altitude using the proposal. This will improve the quality of the manuscript.
During experiments done for this work, we weren’t able to measure actual drone motors speeds, while drone altitude is simply given by applying typical FMCW relations. We wrote in paper the expected maximum-rpms for quadricopter, while for single motor we don’t have such parameter.
Nevertheless in our opinion the aim of actual work is to depict the capability of inferring a meaningful FMCW radar image model for flying UAVs, proving its effectiveness putting model fitting results in comparison with a well-proven mechanical model.
Of course, we agree that this is only the first step in building an effective method for building reliable flying UAV radar fingerprints, but actual correlation results depicted by Confusion-Matrices show that such methodology is meaningful and it can lead to interesting results.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
In this paper Authors, introduce an effective model for the micro-Doppler effect suitable for frequency-modulated continuous-wave (FMCW) radar applications, as well as its exploitation to investigate the UAV signatures. The presented topic is interesting in the field of science and research.
My comments to the article are as follows:
- I propose to extend the Introduction to UAV control issues also with new signals, including electroencephalography, in this respect I recommend referring to, for example: The Use of Brain-Computer Interface to Control Unmanned Aerial Vehicle, Automation 2019: Progress In Automation, Robotics And Measurement Techniques from 2020. This will have a positive effect on updating the bibliography and extending the background of the article.
- I did not find any reference to Figure 4b in the text. Please verify.
- The description of the axes in Figure 5 should be extended to include the measure for the y axis. I propose to write the unit in Fig. 5 as: "kHz", not "KHz".
- I suggest to add a subsection on the Discussion of results to the study. I propose to extract part of the text from the chapter with tables.
- Plans for the future should be included in Conclusion
Author Response
Comments and Suggestions for Authors
In this paper Authors, introduce an effective model for the micro-Doppler effect suitable for frequency-modulated continuous-wave (FMCW) radar applications, as well as its exploitation to investigate the UAV signatures. The presented topic is interesting in the field of science and research.
My comments to the article are as follows:
- I propose to extend the Introduction to UAV control issues also with new signals, including electroencephalography, in this respect I recommend referring to, for example: The Use of Brain-Computer Interface to Control Unmanned Aerial Vehicle, Automation 2019: Progress In Automation, Robotics And Measurement Techniques from 2020. This will have a positive effect on updating the bibliography and extending the background of the article.
A reference to the suggested work has been Included in the revised version, as example of UAVs biomedical application.
- I did not find any reference to Figure 4b in the text. Please verify.
We extended Fig. 4a and 4b description paragraph also introducing more details about MTI algorithm usage. Now both figures are more clearly described also depicting their different underlying scenarios.
- The description of the axes in Figure 5 should be extended to include the measure for the y axis. I propose to write the unit in Fig. 5 as: "kHz", not "KHz".
We corrected figure sizes and we uniformed axial units.
- I suggest to add a subsection on the Discussion of results to the study. I propose to extract part of the text from the chapter with tables.
We tried to write a new Discussion of results paragraph but we found that discussion of results is related to description of tables 2 and 3 in a tight way. By this in our opinion such paragraph would become a replica of concepts already written in subparagraph 3.3, thus it would not introduce useful information despite it would make the overall reading a bit more confused.
- Plans for the future should be included in Conclusion
We expanded Conclusion paragraph highlighting more in detail actual work drawbacks, putting suggestions on next feasible research steps. This considering that actually we are thinking to a “new way” to consider Deep-Learing unsupervised training, thus our final objective is the removal of actual measurements in the building of UAVs fingerprint database.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Appreciate author's revisions. I hope the current manuscript can be accepted.
