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All the reviewers' comments have been addressed carefully and sufficiently, the revisions are rational from my point of view, I think the current version of the paper can be accepted.
The paper has been significantly improved and my concerns have been carefully addressed. I would recommend the paper be accepted for publication.
It is fine.
It is fine.
I would recommend the paper be accepted for publication.
Dear authors,
Reviewers have now commented on your paper. You will see that they advise you to make major revisions to your manuscript. If you are prepared to undertake the work required, I would be pleased to reconsider my decision.
If you decide to revise the work, please submit a list of changes or a rebuttal against each point that is being raised when you submit the revised manuscript.
Best wishes,
D. Pamucar
**PeerJ Staff Note:** It is PeerJ policy that additional references suggested during the peer-review process should only be included if the authors agree that they are relevant and useful.
Please see the enclosed file.
Please see the enclosed file.
Please see the enclosed file.
Please see the enclosed file.
1. English grammar must be improved since several errors appear throughout the text. In many places, the punctuation and spaces after the abbreviations must be corrected carefully.
2. The Abstract should be more application-oriented.
3. The author should add more recent papers in the introduction to help readers better grasp the relevant research trends. For authors’ attention: https://doi.org/10.3390/e25081177
4. Authors should explain one or two applications of this work explicitly in the text of the manuscript so that readers can get it easily.
5. The conclusion section should include the most important results.
6. The authors are requested to give a comparison study of the proposed work with the published ones, and should include some advantages. See https://doi.org/10.3390/s23239386
7. The Title should be revised for a better grasp of the reader.
I hope the author can provide the state estimation diagram (or state tracking diagram) of the system in the simulation to further demonstrate the effectiveness of the algorithm designed in this paper.
This article involves many parameters. How to obtain these parameters? Is there a better way?
Authors are requested to implement all the suggested comments.
The abstract suggests an improvement over state of the art. However, the literature on this problem is huge and goes well beyond variations of the EKF, e.g., using S-estimators, with performance better than usual requirements in aerospace industry. Therefore, the first impact for a reader may be that claims may be questionable (there are no precise statements on how good the proposed system is).
Moreover, the abstract (and the remaining of the paper) use subjective expressions, e.g., "high dynamic conditions", leading the reader to question about the type of rocket being considered (a rocket carrying a payload to Earth orbit is very different from a surface-to-air missile - the example at the end does not suggest such a high dynamics).
The lack of accurate definition of requirements is also present is comments related to the state of the art, e.g., "... rockets with shorter flight durations.", lines 135-136, that is how short is "shorter" ? Is the paper about surface to air missiles, which typically have flight durations in the order of a few dozens of seconds ?
The pdf still has formatting problems, e.g., expressions (1). (2), (3), (5).
Some sentences result strange, e.g., on line 228, "...setting the initial state 1 of the filter...". Does this means state at instant 1 ?
I could not figure out any stage to estimate inertia. In the case of a rocket this is a critical aspect (which has been addressed in the literature).
Typos at line 197, "mat-rix", and in the caption of fig 2. Figure 1 has also problems. In the text, to avoid formatting issues, I suggest that Latex is used.
Even though each of the experiments is, in itself, interesting, the paper does not discuss the need to have two such different scenarios.
For the rocket scenario, explanations on how mass variation is accounted is necessary.
For the car scenario, it is unclear where the "high dynamics" is
Though the result appear to be interesting, it remains to clarify whether the dynamics of the vehicles is time-varying (namely in the case of the rocket).
The validity of the findings remains questionable. They may be relevant for problems with time-invariant or slowly variant dynamics. For time-variant ones the paper needs to explicily address how are they being taken care of.
Dear authors,
One of the previous reviewers has now commented on your paper. You will see that they advise you to make major revisions to your manuscript. If you are prepared to undertake the work required, I would be pleased to reconsider my decision.
If you decide to revise the work, please submit a list of changes or a rebuttal against each point that is being raised when you submit the revised manuscript.
Best wishes,
D. Pamucar
Handling editor’s comments:
The authors mention real-time reconstruction of filter parameters. It is important to provide more details on how this adaptive reconfiguration is implemented. What triggers the reconfiguration, and how does it ensure precise modeling of navigation parameters?
Elaborate on how the system state model was developed to reflect the unique characteristics of the rocket flight environment. What parameters or conditions were considered to ensure rapid convergence of the filtering process?
The AREKF method is said to have lower computational costs. Could you quantify these savings regarding processing time or resource usage compared to traditional EKF and other improved algorithms?
The results from the 6D Model simulation and car-mounted experiments are promising. However, have these results been validated with actual rocket flight data?
The report compares AREKF with traditional EKF and existing improved algorithms. Provide a more detailed comparison, including specific metrics and performance benchmarks.
The authors highlight the method's effectiveness under high-dynamic conditions. Could you define " high-dynamic conditions" in this context and explain how the method adapts to them?
Please see enclosed file.
Please see enclosed file.
Please see enclosed file.
Please see enclosed file.
Dear authors,
Reviewers have now commented on your paper. You will see that they advise you to make major revisions to your manuscript. If you are prepared to undertake the work required, I would be pleased to reconsider my decision.
If you decide to revise the work, please submit a list of changes or a rebuttal against each point that is being raised when you submit the revised manuscript.
Best wishes,
D. Pamucar
See the enclosed file.
See the enclosed file.
See the enclosed file.
See the enclosed file.
1. English grammar must be improved since several errors appear throughout the text. The punctuation and space after the abbreviations must be corrected carefully in many places.
2. The Abstract should be more application-oriented.
3. The author should add more recent papers in the introduction to help readers better grasp the relevant research trends.
4. Authors should explain one or two applications of this work explicitly in the text of the manuscript so that readers can get it easily.
5. The Title should be revised to grasp the reader better.
No comments
1. The authors are requested to mention the novelty of their work in the manuscript so that readers can get it easily.
2. The authors are requested to give a comparison study of the proposed work with the published ones and should include some advantages.
3. The conclusion section should include the most important results.
4. Authors should explain the probability distribution function for the proposed study structure as well as the equations related. It will be very useful.
Finally, I recommend that the paper should be revised taking care of the above comments.
The paper needs a thorough revision of the English writing to improve readability. As it is, some sentences are difficult to understand. Also, the formating has multiple issues (e.g., the title and numbering of the initial section, or using "mems" instead of "MEMS", in p. 2, or using "navigation solving accuracy" instead of "navigation solution accuracy").
Section 1 is difficult to read as multiple variables and subscriptd and superscripts are not adequately explained. This is especially true for expressions (1) - (3).
Expression (5) appears to be poorly formated. Also "q" appears to be nowhere.
The expressions of the EKF are standard. However, "Q" is used as a covariance while previously was used to represent the "conversion quaternions".
In section 1.2, expression (12) is unclear, namely the meaning of "random wandering" (it seems to be related to drift; if that is the case it could be to have some explanation about the conditions that make it a random variable and, if that is the case, (15) is a drift variance ?). I couldn't understand where the adaptation of the filter parameters occurs. It appears to be in (15), after a rough estimate of the variance (14), but the reader must guess where does if influences the filter.
The experimental design is flawed. If the goal is to use the system in a rocket, which is intrinsically a 6D device, it is difficult to understand if the performance of the system when tested in a sports car (essentially a 4D device) can be extrapolated.
The plots are hard to read due to their small dimensions, namely the subplots in figures 3 and 4.
The findings, promising a 80% improvement in position, velocity, and attitude estimation are insufficiently explained. It is unclear how this value was obtained (the filtering in the plots suggest that other basic filtering techniques could be used to obtain similar results). Also, additional experiments are required, namely with a 6D device.
No additional comments
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