In-Motion Coarse Alignment Method Based on Position Loci and Optimal-REQUEST for SINS

Round 1

Reviewer 1 Report

Notes:

- Please improve your writing. Sometimes it gets confusing

- If you define acronyms, please use them e.g. Line 25 and 26

- Sometimes, in the acronyms, you use capital letters on each word, and sometimes you do not. E.g. Global Positioning System (line 27) and global positioning system (line 10)

- Missing a proper RELATED WORK section with the correct citations. This section should be divided into subsections to improve the article's organization

- Where are the citations? All new developments?

- Missing Figures during the article to improve the explanation

Abstract:

- Please quantify the improvement in performance using e.g. percentage

- Why did you only use simulation results? 

- Improve your keywords - e.g. attitude determination is not "attitude estimation"?

Introduction:

- "...radiate energy to the outside" - Please explain better. Why could this be important?

- "In Ref"? (line 41). "Ref"? Why are you using this?

- The explanation is confusing since you do not have a proper RELATED WORK section. The explored algorithms (citations) should have the objective of introducing the topic

- "..this paper extends the 78 research in Ref [21]...." - Why? What are the main differences? What is new?

- Are the contributions complete innovations? Does no other algorithm use that? Or are they simply the extension of Ref [21]?

- Resume the contributions, be more objective in the explanation

Traditional method of in-motion coarse alignment and problem statement:

- Missing a proper section introduction

- Resume the contributions, be more objective in the explanation

- Missing Figures illustrating the explanation

- Integrals in eq. 8? Are you not using a discrete version (sensor measurement)?

- A very small section missing a proper explanation and objectives

The principle of vector observation based on the position loci:

- Always start a section with subsections explaining them (the section content)

- Where are the citations? All new developments?

- To improve article clarity, pass the mathematical formulation to the appendix and improve the section

- Integrals in eq. 11? Are you not using a discrete version (sensor measurement)? You already introduced the equation content, and it is discrete

- Why only the comparison with the REQUEST algorithm? Is it a state-of-the-art algorithm?

Experiment:

- Used performance metrics?

- Processing time? Used computer platform?

- Section objectives? "To verify the performance..." is not enough

- Why only the comparison with the REQUEST and QUEST algorithms? Are they state-of-the-art algorithms?

- Where are the citations? At least for the performance metrics

- You can use box plot graphics to show the error behavior

- Real experiments? 

- Why did you not compare with other algorithms?

- Table 3 - Why does OP-PL have the worst performance in pitch 1 - 150s?

Conclusions and future work:

- Quantify your algorithm increase in performance using e.g. percentage

Author Response

We would like to express our sincere appreciation to you for the constructive yet critical comments and the efforts provided in helping us to improve the quality of the paper further. We hope that our revision could address your concerns.  The detailed responses are attached.

Author Response File: Author Response.pdf

Reviewer 2 Report

This is an interesting contribution to the existing literature, but the paper suffers from several shortcomings listed in the following comments.

-          The paper should be checked by a native.

-          A discussion section should be added.

-          The introduction should be updated by recent researches.

-          The novelty and contribution should be clearly bolded.

-          It’s better to suggest some subjects for future works.

Best regards,

 

Author Response

We would like to express our sincere appreciation to you for the constructive yet critical comments and the efforts provided in helping us to improve the quality and presentation of the paper further. We hope that our revision has addressed your concerns. The detailed responses are shown in the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

This manuscript presents a new in-motion coarse alignment method for the strapdown inertial navigation system (SINS). The authors make use of the position loci obtained from the global positioning system (GPS). They claim that the difference from the typical coarse alignment methods is that the proposed algorithm uses GPS position loci information to form the vector observation. The new algorithm does not use velocity information, expanding the application range of in-motion coarse alignment. In the sequence, the authors utilize the Optimal-REQUEST algorithm to reduce the influence of random errors hiding in the vector observation. This algorithm is adaptive and iterative and can adjust its gain filter according to a loss function. Moreover, a set of simulation results are presented to prove that the proposed algorithm can suppress the impact of random errors and improve the alignment performance compared with similar algorithms.

 

The authors did a good job. Section 1 is comprehensive and gives the reader a good insight into the main topic. It would be more interesting if the authors could split this section into a first part covering the basic definitions, the ones necessary for understanding the readers, and a second one presenting the most relevant related papers. A table synthesizing the similar algorithms' main desired characteristics would increase the manuscript's readability. Section 2 could be incorporated into the new section suggested by me. Section 3 is long, but the presented details are necessary for the reader's complete understanding. The experiment details given in section 4 are optimal; I believe the figures and tables are well constructed. The final section could be improved by an in-depth evaluation of the main proposals presented in the manuscript. The suggestions are not mandatory. I enjoyed reading this manuscript and believe it will contribute to other groups researching the same topic. 

Author Response

We would like to express our sincere appreciation to you for the constructive yet critical comments and the efforts provided in helping us to improve the quality and presentation of the paper further. We hope that our revision has addressed your concerns. The detailed responses are shown in the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

NOTES:

- Still missing a proper "Related Work" section describing the current existing algorithms and applications.

- Some of the comments were not completely addressed by the authors modifying the text accordingly

- Review #1 - Point 4, 8, 10, 11, 13, 14, 25, 26, 27, 28, 29, 31, 32, 33,34 are not correctly addressed or explained

- Additional notes, a "box plot" is not a histogram representation

Author Response

We would like to express our sincere appreciation to you for the constructive yet critical comments and the efforts provided in helping us to improve the quality of the paper further. We hope that our revision could address your concerns. The detailed responses are shown in the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

The paper can be accepted in current form.

Author Response

Thank you very much for your positive comment again.