Indoor and Outdoor Low-Cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System

Round 1

Reviewer 1 Report

Please see the attached file

Comments for author File: Comments.pdf

Author Response

Dear Editor and Reviewers,

RE: Manuscript ID: remotesensing-903308

Thanks very much for your letter and the insightful comments from the reviewers that concerning the manuscript entitled “Indoor and Outdoor Low-cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System”. Those comments are all valuable and helpful for revising and improving this paper, as well as an important guiding significance to our researches in the vehicular navigation field.

We have studied the comments carefully and corrected all of them one by one, which we hope to response the questions of the reviewers and also meet the standards of the Remote Sensing. Moreover, all the revised parts according to the reviewers’ comments are marked with yellow background in the revised and uploaded paper. The main corrections in the paper and the response to the reviewer’s comments are listed as following:

#Review1:

This paper investigates the use of GNSS/INS and LIDAR/INS integration to provide seamless navigation between the indoor and outdoor environments. Here are some comments that might help improve the paper.

Technical comments

1. GNSS lost down not heard of this expression before. If the authors saw this expression in the literature, this is fine; otherwise, I suggest to remove this phrase.

---Response: Thanks for your suggestion, the inaccurate phrases are all corrected in the latest version of the paper.

2. The introduction section talked about indoor navigation techniques such as WiFi, UWB, and LIDAR. However, it did not mention other research papers discussing the main topic of the paper, which is INS/GNSS/LIDAR integration such as “K.W. Chiang, G.J. Tsai, H.W. Chang, C. Joly, N. EI-Sheimy, “Sealmess navigation and mapping using an INS/GNSS/grid-based SLAM semi-tightly coupled integration scheme”, Information Fusion, Volume 50, 2019, Pages 181-196, ISSN 1566-2535, https://doi.org/10.1016/j.inffus.2019.01.004”and other research papers utilizing LIDAR/INS/GNSS integration in different navigation applications.

---Response: Thank you for your suggestion. We have carefully read your recommended reference and added it to the reference of the updated manuscript. The recommended article has a strong correlation with the content of our article, and the final positioning result of the article. The accuracy is high. However, this article using high-precision and expensive navigation systems that based on the integration of INS (C-MIGITS) and LIDAR (VLP-16), which is mainly focuses on the high-end application requirements. While our manuscript focuses on the use of the low-cost inertial navigation sensor (MPU9250), and also solving the navigation mode switching problem, which is mainly focuses the application of low-end application such as the underground parking lot navigation

3. In the experimental section, the results are based on comparing the INS/LIDAR solution to the INS only solution. It is well-known that a DR solution will drift if it was not supported by other systems. It is also surprising to see the reference in the comparison is the LIDAR-only solution. If the LIDAR-only solution can work well indoors, why the integration with INS? In this case, the results show that the INS worsen the LIDAR solution. Something is missing here. Some points have to be clarified:
4. The paper should introduce and demonstrate with the results, what are the benefits of the INS to the LIDAR solution (e.g., smoothing, areas where LIDAR did not work well, etc.). Also, the paper should highlight what is new in this paper compared to other research on INS/LIDAR/GNSS integration?

---Response: Thank you for your suggestion. The biggest advantage of INS/LIDAR integrated navigation compared to single LIDAR navigation is to enhance the trajectory and reduce the impact of trajectory mutation errors. We will add the above content to the introduction part of the latest paper and highlight the innovation of the switching navigation algorithm in it.

1. The reference cannot rely only on the same LIDAR used for integration. It should be obtained from an integrated LIDAR/INS solution using a high-end INS or at least from a higher quality LIDAR. It must be an external source of data.

---Response: Thank you for your suggestion. This article describes the existing problems. The experiment part of this article uses indoors and performs tracking and navigation according to the calibration trajectory prepared in advance. The standard trajectory referenced in this experiment is the calibration trajectory. The description of the problem here will be revised in the 3.2 Section of the latest manuscript.

4. The authors mentioned that they chose the Hector SLAM algorithm because it does not utilize the odometer; however, in the paragraph following equation (14), it was mentioned that the speed is obtained from the odometer. This part needs to be clarified.

---Response: Based on the Hector SLAM algorithm, it does not need an odometer to generate a two-dimensional flat map and generate a vehicle's trajectory. The main function of Vt is to integrate the more accurate vehicle position to assist the vehicle INS navigation system in the integrated navigation algorithm. The description of the problem here will be revised in the 2.2 Section of the latest manuscript.

5. The main application for the developed system is vehicular navigation. The authors mentioned that cost consideration resulted in using a robot to simulate the vehicle motion. Robots are typically much slower than vehicles, and the dynamics indoors and outdoors would be different. In Experiment 1, the authors tried to prove that the robot system is behaving like a vehicle, but the speed in Fig.4 is very low compared to a slow vehicle entering a garage. The speed values are missing in the other experiments. I believe more discussion is needed to verify how the simulation system can be applied to vehicle navigation and what are the possible limitations.

---Response: Thank you for your suggestion. We think the limitation of the vehicle here is only to reduce the speed of the vehicle when the LIDAR is used. When the vehicle is driving outdoors, the vehicle only needs to use GNSS/INS integrated navigation, where the vehicle speed does not limit the positioning accuracy of the vehicle navigation system. When the vehicle enters the garage, slowing down and driving at a low speed are necessary for the vehicle to enter the small garage (vehicles in underground garages in China will require a speed limit of 5km/h). Therefore, there is no specific explanation for the speed of the vehicle in this manuscript. We will add these instructions in the latest manuscript to make the it more rigorous.

6. The results in Fig.1 is not clear. The door should be in front of the robot, but in which direction? I think the door should be marked in the figure. Also, what does the door flag points mean?

---Response: Thank you for your suggestion, we think you should refer to Figure 6 instead of Figure 1. For Figure 6, We have added a clear sign of the true position of the door in the latest manuscript so that readers can understand the picture more easily. In addition, the door detection point is the door detection mark obtained after We used the door detection equation listed above in my experiment. The yellow detection mark can prove the usability and effectiveness of the door detection algorithm.

7. Fig. 12 compares the DR solution to the INS/LIDAR solution; nevertheless, the two buildings and trajectories look different, how?

---Response: Thank you for your suggestion. Figure 12 is two different experiments conducted on the same venue, but the angles of the two figures are slightly different. In fact, they are in the same building. At the end of this paper, the reliability and stability of the whole set of algorithm processes are verified through two complete integrated navigation and switching navigation experiments from outdoor to indoor. When the GNSS navigation signal becomes blurred, the switching algorithm can switch the system to the indoor navigation mode in time to avoid the increase of divergence of navigation and positioning errors.

8. In Table 1, it was mentioned that it is for the three experiments; how was the average standard deviation calculated? I prefer to make it on just the last experiment; especially it has everything. Also, what does the number (300s) represent in the DR line? More importantly, showing that LIDAR/INS integration is better than an INS-alone is not a new contribution, as discussed earlier.

---Response: Thank you for your suggestion. The standard deviation here is the standard deviation calculated by squaring the latitude and longitude position coordinates of the tested trajectory and the standard trajectory and then taking the square root. Because of the previous ill-consideration, the specific location and route of the standard trajectory are not specified here, so there will be a lot of ambiguity. We have changed a lot of trajectory diagrams in the latest manuscript to correct this vague problem. (300s) is the time for the simulated robot to run indoors. It was originally intended to be distinguished from the outdoor navigation part, but this is indeed not very necessary and will cause ambiguity, so we have removed this description in the latest manuscript.

9. In section 2.3, the authors mentioned “or” and “any of ” when talking about the three conditions in equation(25). I think it should be “and”, which means all the three conditions are satisfied. Otherwise, if only the pitch condition can activate the transition, how will the system behave if, in an outdoor situation, the vehicle is moving down a bridge with low speed due to traffic conditions (a pitch angle like a garage)? Will the system enter the indoor mode?

---Response: We are very glad to see you ask such a profound question about our algorithm. This equation is the conclusion drawn by our team after many experiments and analysis. We are very happy to discuss it with you. From the conclusion, we believe that the effect of “or” is better than “and” in this switching. Using the ramp to detect and confirm that the vehicle enters the garage is the second part of the switching algorithm. Because of the first step of the pre-judgment, the misdetection of the ramp caused by the vehicle vibration will be effectively shielded. In addition, due to the problem of GNSS signal ambiguity, the GNSS signal will disappear completely after the vehicle enters the garage 10s-15s. Satellite data can still be sent and received normally during the GNSS signal blurring stage, but the positioning information has a large deviation from the actual position data, but this process of increasing error cannot be reflected in the GNSS data in time, so the detection signal of the ramp and LIDAR will generally be early Signals for satellite positioning data loss. If the “and” detection is used here to meet the requirements of switching the vehicle navigation state at the same time, it will greatly increase the positioning error of the indoor navigation.

10. - Indeed, the authors

utilized a low-cost IMU and GNSS receiver. The LIDAR is typically not a low-cost device. The one utilized in this work is a relatively low-cost one (a few hundred dollars). This should be mentioned in the system description so that the reader can understand what level of cost the system is targeting.

---Response: Thank you for your suggestion. We think that the multi-line LIDAR used by unmanned vehicles, such as 16-line and 32-line LIDAR, is indeed very expensive. The price is usually US$ 3000 or even more. However, this experiment uses a single-line LIDAR. The cost of this kind of LIDAR is relatively low. The unit price is about $100, and there is a trend of further price reductions. Under this trend, it will be extremely popular in the future and become a general low-cost navigation sensor, so we chose this experimental device for this experiment.

General comments

1. The Language of the paper needs careful revision. There are lots of typos, grammatical errors, and incorrect sentences.

---Response: Thank you for your suggestion. We will strictly modify this manuscript carefully and continue to improve our English writing skills.

2. There should be a space between the brackets of the reference citation and the previous word (e.g., positioning [1]) and also before all the abbreviations (e.g., global navigation satellite system (GNSS)). These spaces are missing in the whole paper, so please add them.

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

3. Reference [24] is cited after reference [4]!! Consider citing reference [24] as [5] and shift all the subsequent references by 1.

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

4. In Figure.1,
5. “GNSS position receiver”---“GNSS receiver”
6. ”Position velocity updated”----“Position and velocity update”
7. “Relative position updated”----“Relative position update”

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

5. In equations (7) and (8),
6. Define the terms.
7. The notation is unclear. I believe only is the quaternion vector. What does (Re) mean? Is it a rotation matrix between two frames? Is it the real component? Please elaborate.
8. I suggest differentiating between the angular rate and the noise symbols by using the Greek letter for the angular rotation and the English letter for the noise terms.

---Response: Thank you for your suggestion to this equation, because we considered that this is not the focus of this manuscript, so we want to omit some non-main content and highlight the key switching algorithm, so Equation (7) and (8) are omitted. After requiring your suggestions, we decided to add these necessary equations to make the manuscript more complete. In addition, the use of noise symbols is really easy to confuse readers with angular velocity symbols. We will correct this problem in the new manuscript.

6. The caption of Fig.7 and Fig.8 should state ”the first part of second experiment”. Also, Fig.9 and Fig.10 should state “the second part of the second experiment”.

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

7. What does L1, L2, L3, and L4 mean in the legends of Fig. 8 and Fig. 10?

--Response: L1, L2, L3 is the codename is my experiment, they are corrected in the latest version of the paper, thanks for your advice.

8. The caption of Fig.12 should state “the third experiment”

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Editor,

my suggestion and comment for authors:

1. In Abstract please add information about obtained results from the research test. IT is a base part of the Abstract.
2. All acronyms must be explained in the paper.
3. what means "M(Si...)" in equation (1) ?
4. what means "n" in equation (1) ?
5. Page 6, it should be: "frame. The system attitude quaternion.."
6. Page 6, it should be: ". The gyroscope static drift derivative"
7. what means "-g" in equation (7) ?
8. All symbols from equations (15_16) must be explained in the text.
9. All symbols from equations (22-23) must be explained in the text.
10. All symbols from equations (24-25) must be explained in the text.
11. page 9, what means "entrance. l,t are"?
12. All symbols from equations (26-30) must be explained in the text.
13. Figure 8, what is the value of unit in Y axis? How you calculated the Standard deviation term?
14. Figure 10. The same problem, see comment 13.
15. Discussion, What is a novelty of paper with reference to past research from References? Please discuss about it in paper.
16. Conclusions. Please clearly write about the final results from the research test. What i as a final accuracy of the presented method?

In my opinion, paper must be modified and corrected.

Author Response

Dear Editor and Reviewers,

RE: Manuscript ID: remotesensing-903308

Thanks very much for your letter and the insightful comments from the reviewers that concerning the manuscript entitled “Indoor and Outdoor Low-cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System”. Those comments are all valuable and helpful for revising and improving this paper, as well as an important guiding significance to our researches in the vehicular navigation field.

We have studied the comments carefully and corrected all of them one by one, which we hope to response the questions of the reviewers and also meet the standards of the Remote Sensing. Moreover, all the revised parts according to the reviewers’ comments are marked with yellow background in the revised and uploaded paper. The main corrections in the paper and the response to the reviewer’s comments are listed as following:

#Review2

Comments and Suggestions for Authors

Dear Editor,

my suggestion and comment for authors:

In Abstract please add information about obtained results from the research test. IT is a base part of the Abstract.

---Response: Thank you for your suggestion. We will focus on adding a description of the experimental results and innovations in the new paper, and modify the vague words used in the previous description, so that the abstract part of the manuscript is more distinct and the theme is more convenient. The reader understands the main point of the manuscript.

All acronyms must be explained in the paper.

what means "M(Si...)" in equation (1) ?

---Response:    represents the grid map value of coordinates . They are corrected in the latest version of the paper.

what means "n" in equation (1) ?

---Response: n is the number of the grid points. They are corrected in the latest version of the paper.

Page 6, it should be: "frame. The system attitude quaternion."

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

Page 6, it should be: ". The gyroscope static drift derivative"

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

what means "-g" in equation (7) ?

All symbols from equations (15_16) must be explained in the text

All symbols from equations (22-23) must be explained in the text.

All symbols from equations (24-25) must be explained in the text.

---Response: Thanks for your suggestions, “g” is the symbol of gravity constant. I have added the explanation of the corresponding equations in the latest version of the paper, which will make my manuscript more complete and more readable.

page 9, what means "entrance. l,t are"?

---Response: l and t are two variables in Equation (31).

All symbols from equations (26-30) must be explained in the text.

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

Figure 8, what is the value of unit in Y axis? How you calculated the Standard deviation term?

Figure 10. The same problem, see comment 13.

---Response: The standard deviation here is the difference between the latitude and longitude coordinates of the specified route of the simulated robot and the actual driving route, which is obtained by squaring and then rooting. Therefore, the unit of mean square error here should be meters. We are already in the latest version. This question was revised in the manuscript, thank you for your detailed suggestions.

Discussion, what is a novelty of paper with reference to past research from References? Please discuss about it in paper.

Conclusions. Please clearly write about the final results from the research test. What i as a final accuracy of the presented method?

---Response: Thanks for your suggestion, we have rewritten the conclusion of the manuscript and the discussion part of the reference according to your requirements, so that the innovations and experimental results of this article are more vivid, easy to read and understand, and at the same time the effect of the experiment The label of the reference trajectory is added to the figure to make the experimental results more clear.

In my opinion, paper must be modified and corrected.

Author Response File: Author Response.pdf

Reviewer 3 Report

In this paper, the low-cost multi-sensor integrated navigation scheme can effectively solve and supplement the problem of missing positioning signals from outdoor to indoor.

It is very interesting and important work as it will to solve the problem of missing positioning signals by using appropriate algorithms.

The authors are presented analytically the previous researches about the use of different algorithms. According to the authors the results proved that the multi-sensor integrated seamless navigation algorithm is a stable and reliable algorithm with high positioning accuracy

Comments

1. The subject of the paper should be clearer in the abstract
2. in the paragraph 2.1 (LIDAR Navigation Algorithm Model) most references are needed
3. in the equation 2, what is the angle θ?
4. in the equation 6 what is angle φ? The angle φ is the same of the angle θ and angle ψ?
5. in the line 138 the authors told that ²the speed of the vehicle has to be controlled in a low level so that it will have an ideal drawing². In my opinion must be set the low level
6. in the equation 18, what is the term of Γ_Κ-1?
7. it is better to use the symbol Φ(k)  for latitude and Λ(k) for longitude
8. in the equation 29, what is the term of  λ?
9. which is the cost of this robot that used in the experiments?
10. in line 214 the authors told that ² When the vehicle runs in low velocity and deceleration state². In my opinion must be set the low velocity
    
    
11. in the line 219 the term sky direction must be changed

   12. The standard deviation error of the positioning error must have units. Please correct this in the figures.

13. the conclusions are very shortly. Must be rewritten and to present in more detail & specifically the results of the.

14. In my opinion the should use a list of the symbolism they use in their work, such as the abbreviations.

Comments for author File: Comments.pdf

Author Response

Dear Editor and Reviewers,

RE: Manuscript ID: remotesensing-903308

Thanks very much for your letter and the insightful comments from the reviewers that concerning the manuscript entitled “Indoor and Outdoor Low-cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System”. Those comments are all valuable and helpful for revising and improving this paper, as well as an important guiding significance to our researches in the vehicular navigation field.

We have studied the comments carefully and corrected all of them one by one, which we hope to response the questions of the reviewers and also meet the standards of the Remote Sensing. Moreover, all the revised parts according to the reviewers’ comments are marked with yellow background in the revised and uploaded paper. The main corrections in the paper and the response to the reviewer’s comments are listed as following:

#Review3:

In this paper, the low-cost multi-sensor integrated navigation scheme can effectively solve and supplement the problem of missing positioning signals from outdoor to indoor. It is very interesting and important work as it will to solve the problem of missing positioning signals by using appropriate algorithms. The authors are presented analytically the previous researches about the use of different algorithms. According to the authors the results proved that the multi-sensor integrated seamless navigation algorithm is a stable and reliable algorithm with high positioning accuracy

---Response: Thank you very much for your evaluation of this article. We will better improve the practical value and writing level of our research project based on your revised comments.

Comments

1. The subject of the paper should be clearer in the abstract

---Response: Thank you for your suggestion. We will focus on adding a description of the experimental results and innovations in the new paper, and modify the vague words used in the previous description, so that the abstract part of the manuscript is more distinct and the theme is more convenient. The reader understands the main point of the manuscript.

2. in the paragraph 2.1 (LIDAR Navigation Algorithm Model) most references are needed

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

3. in the equation 2, what is the angle θ?

---Response: The  is the rotation angle for vector. They are corrected in the latest version of the paper.

4. in the equation 6 what is angle φ? The angle φ is the same of the angle θ and angle ψ?

---Response: Thank you for your suggestion. There is some confusion during the use of symbols in this article. We finally re-edited this symbol and wrote a unified result. They will be updated in the latest article.

5. in the line 138 the authors told that the speed of the vehicle has to be controlled in a low level so that it will have an ideal drawing. In my opinion must be set the low level

---Response: Thank you for your suggestion. It may be that the content described in this article is not accurate. Because the Hector SLAM algorithm does not introduce odometer variables, the update of the map requires the LIDAR data of the current frame and the previously generated map. Data matching, collecting LIDAR data at too fast speed will inevitably lead to data matching distortion, so it is necessary to use "must" according to your suggestion.

6. in the equation 18, what is the term of Γk −1 ?

---Response: Sorry, the form of the equation is wrong. There were extra variables when editing the equation. Thank you for pointing out this major problem. We updated this equation in the latest article and double-checked all the problems here.

7. it is better to use the symbol Φ(k) for latitude and Λ(k) for longitude

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

8. in the equation 29, what is the term of λ?

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

9. which is the cost of this robot that used in the experiments?

---Response: The robot in the experiment cost about US$1200, but this robot is not specially designed for this experiment. Therefore, sensors that are not related to this experiment, such as cameras, are also installed on the robot. This robot did not purchase hardware and mechanical structure according to the low-cost design in the paper. The robot aims to verify the usability test of low-cost inertial navigation and low-cost LIDAR navigation in underground garages. The total cost of the navigation equipment described in this paper is Within $200 US dollars.

10. in line 214 the authors told that ² When the vehicle runs in low velocity and deceleration state². In my opinion must be set the low velocity

---Response: Thank you for your suggestion. This question is similar to Question 5. We will revise the vague expression in the paper according to your comments to make the article more clear.

11. in the line 219 the term sky direction must be changed

---Response: Thank you for your suggestion, this is a serious mistake, the ground direction is Z axis. We need to double check the direction of this axis.

12. The standard deviation error of the positioning error must have units. Please correct this in the figures.

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

13. the conclusions are very shortly. Must be rewritten and to present in more detail & specifically the results of the.

---Response: Thanks for your suggestion, they are corrected in the latest version of the paper.

14. In my opinion the should use a list of the symbolism they use in their work, such as the abbreviations.

---Response: Thank you for your suggestion. We have added a list of abbreviations at the end of the manuscript to make it easier for readers to find.

Author Response File: Author Response.pdf

Reviewer 4 Report

This paper proposes an indoor integrated navigation system.  The experiments are well realized and the results are attractive (although the chosen reference (LIDAR based) is problematic), but it is not clear what the original contribution is, and how it relates to previous literature (which in this case, is very large). What problem does it solve? How was this problem approached before? What is new in this paper that was not done before?

From section 2.3 it looks like it is a refinement in the switching algorithm, but it is hard to tell.  What the paper never says is why we need a switching algorithm.  It seems that it would be better to simply use an integrated solution always.

Detailed comments (not exhaustive)

Abstract: It needs to be re-organized and re-written to clearly state what problem is being tackled, what the contribution of the paper is, how it is being evaluated.  The elements are there, but it is very unclear.  This is partly due to the grammar but not only.   From what I could understand, the main contribution seems to be the switching algorithm, but I am not sure.

Lines 19-104: needs to be re-written, there are many repeated statements, and it should be summarized further.  It is not clear which algorithm or framework was finally retained for the paper, or what the contribution is with respect to the previous literature.  The abundance of “however” makes it sometimes hard to follow what is a review of previous work and what is going to be used in the paper. 

Lines 105-178: The content of this section seems to be very standard (at least up to 2.2).   For 2.3, the authors have described a switching algorithm elsewhere ([21] and [23].  From the description, it is not clear what is new.  In any case, the proposed algorithm seems to be very tailored to the experiment.

Line 267: The paper uses the LIDAR track as truth, and then compares the LIDAR/INS to the DR system.  If the LIDAR is assumed a priori to provide the truth, the experiment is only testing the difference between the two systems.  That may not be the case, but the paper is very unclear about this.

Lines 315-326: This paragraph does not belong in the conclusion.  The content of it has been stated several times above.  Conclusions should succinctly state the main contributions and result of the paper.   The conclusions of the paper are far too general and vague.

Author Response

Dear Editor and Reviewers,

RE: Manuscript ID: remotesensing-903308

Thanks very much for your letter and the insightful comments from the reviewers that concerning the manuscript entitled “Indoor and Outdoor Low-cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System”. Those comments are all valuable and helpful for revising and improving this paper, as well as an important guiding significance to our researches in the vehicular navigation field.

We have studied the comments carefully and corrected all of them one by one, which we hope to response the questions of the reviewers and also meet the standards of the Remote Sensing. Moreover, all the revised parts according to the reviewers’ comments are marked with yellow background in the revised and uploaded paper. The main corrections in the paper and the response to the reviewer’s comments are listed as following:

#Review4:

This paper proposes an indoor integrated navigation system.  The experiments are well realized and the results are attractive (although the chosen reference (LIDAR based) is problematic), but it is not clear what the original contribution is, and how it relates to previous literature (which in this case, is very large). What problem does it solve? How was this problem approached before? What is new in this paper that was not done before?

---Response: Thank you for your suggestion. This article is based on the previous low-cost GNSS/INS underground garage integrated navigation algorithm. In this research, the LIDAR sensor is mainly introduced. The new sensor is used for INS navigation inside the garage. The algorithm provides a more reliable reference basis. In the Kalman filter algorithm, it replaces the outdoor navigation GNSS system in the form of observations. On the other hand, LIDAR can play an important auxiliary role in the navigation switching algorithm when the vehicle enters the garage. This article proposes a more general single-line LIDAR door detection algorithm, which can quickly find the location and angle of the garage entrance when the vehicle enters the garage. Compared with the previous detection algorithm that uses vehicle speed and ramp, the vehicle storage success rate is increased by 30%.

From section 2.3 it looks like it is a refinement in the switching algorithm, but it is hard to tell.  What the paper never says is why we need a switching algorithm.  It seems that it would be better to simply use an integrated solution always.

---Response: Thank you for your suggestion. The main reason for using the switching algorithm is that GNSS will enter a period of fuzzy positioning when the vehicle enters the garage, and then the signal will disappear. The positioning errors will occur in the data during the GNSS signal ambiguity stage, leading to errors in indoor navigation. In order to avoid accumulated errors leading to indoor navigation mistake, it is necessary to switch to the LIDAR integrated navigation mode at the entrance of the garage before the GNSS signal disappears completely, which will minimize the navigation error. We will add this description in the latest article, which makes my article's problems to be solved more clearly.

Detailed comments (not exhaustive)

Abstract: It needs to be re-organized and re-written to clearly state what problem is being tackled, what the contribution of the paper is, how it is being evaluated. The elements are there, but it is very unclear. This is partly due to the grammar but not only. From what I could understand, the main contribution seems to be the switching algorithm, but I am not sure.

---Response: Thank you for your suggestion. The main contribution of this article is the switching algorithm part of the navigation. We will revise the abstract part of this manuscript to make the purpose and results of the article clearer.

Lines 19-104: needs to be re-written, there are many repeated statements, and it should be summarized further.  It is not clear which algorithm or framework was finally retained for the paper, or what the contribution is with respect to the previous literature. The abundance of “however” makes it sometimes hard to follow what is a review of previous work and what is going to be used in the paper.

---Response: Thank you for your suggestion. We will focus on revising the introduction part in the latest version of the manuscript. The introduction of references will be clearer and more prominent.

Lines 105-178: The content of this section seems to be very standard (at least up to 2.2).   For 2.3, the authors have described a switching algorithm elsewhere ([21] and [23].  From the description, it is not clear what is new.  In any case, the proposed algorithm seems to be very tailored to the experiment.

---Response: Thank you for your suggestion. Compared with the previous work, this article mainly introduces LIDAR sensors. Because the introduction of new sensors not only improves the positioning accuracy of underground garage navigation, but also upgrades the algorithm for switching navigation. The introduction of new sensors provides more diversified methods for switching navigation algorithms, and at the same time greatly improves the success rate of switching navigation. The main innovation of this article is also derived from here.

Line 267: The paper uses the LIDAR track as truth, and then compares the LIDAR/INS to the DR system.  If the LIDAR is assumed a priori to provide the truth, the experiment is only testing the difference between the two systems.  That may not be the case, but the paper is very unclear about this.

---Response: Thank you for your suggestion. This article describes the problems. The experiment part of this article uses indoors, and the tracking navigation is carried out according to the calibration trajectory prepared in advance. The standard trajectory referred to in this experiment is the calibration trajectory. The description of the problem here will be revised in the latest manuscript.

Lines 315-326: This paragraph does not belong in the conclusion. The content of it has been stated several times above. Conclusions should succinctly state the main contributions and result of the paper. The conclusions of the paper are far too general and vague.

---Response: Thank you for your suggestion. The conclusion narrative in this paragraph does have problems with unclear conclusions. We will modify the problems in the latest article greatly to increase the contribution of this article and the final effect of the experiment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Please see the attached file

Comments for author File: Comments.pdf

Author Response

Response to the Editor and Reviewers

Dear Editor and Reviewers,

RE: Manuscript ID: remotesensing-903308

Thanks very much for your letter and the insightful comments from the reviewers again. Those comments are all valuable and helpful for revising and improving this paper, as well as an important guiding significance to our researches in the vehicular navigation field. We will revise these problems carefully and complete the paper perfectly. Thanks again for your detailed and valuable reviews.

The authors made an excellent effort to improve the paper; however, I still have some comments on the revised manuscript.

1 The addition of the standard reference trajectory is good, but it is still not clear how it is calculated. The added phrase "The red line is the pre-calibrated indoor trajectory according to the longitude and latitude of the building, and it is regarded as the standard reference" is not clear. How did you obtain the latitude and longitude of the building? Since the presented standard deviation (SD) values are in the decimeter level, how did you know or calibrate the actual path inside the building (distance from the walls)? Was it measured manually? Please elaborate on this part.

---Response: Thank you for your suggestion. The calibration method of red line trajectory has been added in the latest manuscript. The modified parts have been marked with yellow in the latest manuscript.

2. 
   The authors mentioned, in reply to the previous comments, that the SD values are
   calculated with respect to the standard trajectory. This should be mentioned clearly in the text, so the reader knows how this SD is calculated.

---Response: Thank you for your suggestion. We have added these contents in the latest manuscript and optimize the relevant paragraph again. The modified parts have been marked with yellow.

3. 
   The authors added the benefits of LIDAR/INS integration over LIDAR-only navigation on page 5, lines 167-169. Nevertheless, in the experiment's discussion, there is no reflection
   on these benefits. The LIDAR solution on the graphs (green) looks very close to the
   integrated yellow solution. There is no comment on the LIDAR-only performance, was the SD worse than the integrated solution? Why is it not mentioned in Table 1? Can you plot the errors or highlight any part of the trajectory that shows the advantages of the integration with the INS (smoothness or/and continuity)?

---Response: Thank you for your suggestion. We have added new contents about the INS in the latest manuscript. The modified parts have been marked with yellow.

4. In Fig. 12, my comment was on how Fig. 12 is a comparison while the two subfigures look different? The authors' reply was, "Figure 12 is two different experiments conducted on the same venue, but the angles of the two figures are slightly different. In fact, they are in the same building. At the end of this paper, the reliability and stability of the whole set of algorithm processes are verified through two complete integrated navigation and switching navigation experiments from outdoor to indoor." If this is true, this means that indeed these are two different trajectories, and the caption is wrong and should be re-written to reflect the above reply.

---Response: Thank you for your suggestion. I will use sub-headings (a) and (b) to explain this experiment with the same purpose according to your latest opinion, so that readers can more clearly know the goal of the experiment and the conclusion.

5. 
   Also, in Fig 12-A, if this is a different test for the integrated algorithm, then the legend "DR trajectory" in Fig12-A is wrong, and it should be "INS/LIDAR trajectory." If it is a DR solution from a different experiment than Fig12-B, so, there is no meaning for the comparison.

---Response: Thank you for your suggestion. The DR navigation trajectory in the part is a mistake. In fact, I used the INS/LIDAR integrated navigation method for the two experiments. The purpose is to verify the stability of the navigation algorithm with two experiments. However, the same experiment twice is really unnecessary and redundant. I will delete one of the trajectory graphs to make the navigation result clearer.

6. 
   Is there is an explanation of why the solution in Fig12-A, before and after the door, is far from the standard trajectory and not like the other figures, even with the DR solution?

---Response: Thank you for your suggestion. The result of Figure 12 (a) is the trajectory obtained from the INS/LIDAR integrated navigation algorithm. The vehicle deviates from the standard trajectory at the door. The deviation of the standard trajectory is because unreasonable control causes errors. So, the Figure 12 (a) does have many problems.

7. 
   In the added paragraph, page 3, line 99, it is not a good practice to mention the researcher's names with the adopted citation style. You can say, "The research in [15] …..." “In [16],...”.

---Response: Thank you for your suggestion. We will pay attention to this detail in the following research and papers, and correct this paragraph in our manuscript. The modified parts have been marked with yellow in the latest manuscript.

8. 
   There should be a space between the brackets of the reference citation and the previous word before all the abbreviations (e.g., global navigation satellite system (GNSS)). The authors fixed this part in the abstract, but the rest of the paper still has the same issue.

---Response: Thank you for your suggestion. We will pay attention to this detail in the following research and papers, and correct this paragraph in our manuscript.

9. The language still needs careful revision. Some software like Grammarly (there is a free version) can help to fix part of these errors. Here are just a few examples of these errors,
   a. Page 3, line 112, "In the this research, …".
   b. Page 6, line 176, "Since the integrated navigation system needs to relation contact
   communicate with various subsystems …"
   c. Page 14, line 289, "And the vehicle will rely on the inertial navigation …". You
   cannot start a sentence with And.
   d. Page 2, lines 38-39, "Therefore, …... paper [4]". The whole sentence needs to be
   re-written.

---Response: Thank you for your suggestion. We will try to use the software that you recommend to modify our article. At the same time, we are also actively seeking help from other colleagues in English and improving our English skill.

Author Response File: Author Response.pdf

Reviewer 2 Report

I accept the paper. 

Author Response

Thank you for your suggestion. We are actively seeking help from other colleagues in
English and improving our English skills. The modified parts have been marked with yellow in the latest manuscript .