Beamspace Scene Classification Algorithm for Low-Angle Estimation in MIMO Radar
Round 1
Reviewer 1 Report
The paper presents the mathematical derivation and application of a low-angle estimation algorithm for MIMO radars using beamspace scene classification. It is well structured and has an extensive introduction that reviews and compares previous developments in low-angle estimation algorithms. Comparison with two other related algorithms shows the performance of the presented algorithm in numerical simulation. Using the Cramer-Rao lower bound, the selected examples show the improvement when the new algorithm is applied.
The paper in its current form needs some minor improvements to be considered for publication.
- Please use a separate paragraph e.g. at the end of the Introduction to introduce all mathematical notations used. This facilitates the reading flow. Please also improve the notation of matrix row and column indexing (e.g. in line 184)
- In some equations, proper fractions should be used to increase readability and comprehensibility (instead of '/', e.g. in line 161).
- Using exp instead of e^(...) would benefit the readability of some equations as well (e.g. in line 158/159).
- Please revise the presentation of the algorithm (line 413) into a shorter, easier to understand form (e.g. in the form of an UML diagram).
If the changes are applied, the findings of this elaboration will be able to contribute well to further research.
Author Response
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Author Response File: 
Author Response.docx
Reviewer 2 Report
This paper explains low angle MIMO estimation in radars and thus develops BSC algorithm. Overall the paper is well written and the introduction is much detailed. what about scattering and diffraction at fig. 1? equation (1) must be referenced. Make equation (23) in compact form. the proof of claims should be shifted to appendix by defining at the end. this is a simulation based paper and we need some scenarios to be validated practically in order to verify such complex equations. Mere accepting simulations may not always be correct and sometime it also ignore a lot of unusual effects. thanks
Author Response
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Author Response File: Author Response.docx
Reviewer 3 Report
The topic of this paper is interesting and in general the paper is well written and organized. However some issues should be clarified. The main reviewer concerns are summarized as follow,
- The main reviewer concern is the novelty of the proposed work concerning [26] of the same authors, since some parts are from this reference, e.g. Proof of Claim 1. Please clearly explain the novelty regarding [26].
- The reviewer suggest to add in the end of Introduction the notation followed in this work since this helps to follow the paper.
- In the Results Section it is mentioned “These experiments are all performed using MATLAB R2021b on a PC with an AMD R7-5800H processor, a 3.20 GHz core frequency, and 16G of RAM”. Are this information relevant to obtain the results? Would the results be different with a PC with other features and other MatLab version?
- 9. Personally I do not like to see results in terms of CPU time since it is highly dependent of the PC features. Besides, the complexity analyses is already given in section 4.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Round 2
Reviewer 2 Report
thanks for revision.
You can carry on the experimental suggestions in your future work.
All other comments are well addressed.
Reviewer 3 Report
The authors have satisfactory addressed the reviewer concerns.
