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Technical Note
Peer-Review Record

Robust GNSS Positioning Using Unbiased Finite Impulse Response Filter

Remote Sens. 2023, 15(18), 4528; https://doi.org/10.3390/rs15184528
by Jie Dou 1, Bing Xu 2 and Lei Dou 1,*
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3:
Reviewer 4:
Remote Sens. 2023, 15(18), 4528; https://doi.org/10.3390/rs15184528
Submission received: 28 July 2023 / Revised: 6 September 2023 / Accepted: 12 September 2023 / Published: 14 September 2023
(This article belongs to the Special Issue GNSS Advanced Positioning Algorithms and Innovative Applications)

Round 1

Reviewer 1 Report

This paper proposes an alternative GNSS solution method to least squares (LS) and Kalman filter (KF), based on an unbiased finite impulse response (UFIR). The proposed method possesses two main advantages: independence from noise statistics and consideration of historical information to estimate the current state. The results presented in this paper are promising; nonetheless, this method may present some critical limitations for real-time/high-precision navigation in terms of computational effort and positioning accuracy.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

General:

1. What is the main question addressed by the research? GNSS analysis 2. Do you consider the topic original or relevant in the field? Does it address a specific gap in the field? Yes 3. What does it add to the subject area compared with other published material? Yes 4. What specific improvements should the authors consider regarding the methodology? What further controls should be considered? See below 5. Are the conclusions consistent with the evidence and arguments presented and do they address the main question posed? Yes 6. Are the references appropriate? See below

 

Comment:

1. One more keyword can be added in abstract.

2. "possesses two main ... the UFIR framework". This sentence should be last in abstract.

3. Chapter 3: Optimization. Could you explain in details regarding optimization method used in your research.

4. Please elaborate more of your results. Especially the analysis part.

5. Noise analysis is not included in this manuscript. Please consider this too.

6. 10/27 = 37% of your references is out-of-date. Please reduce until <20%

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

The paper has a proper writing structure and scientific content. The topic evaluated in the paper is very important and its results are very practical. The results of the paper also show the importance of the research topic. But there are some minor issues that need to be edited:

1.      Please mention and interpret important numerical and statistical results of the paper in the abstract.

2.      The introduction of the paper has been revised and similar researches of recent and more recent years should be mentioned.

3.      The results related to the figures should be interpreted and compared more accurately, and interpretations should be provided based on statistical and numerical parameters.

4.      In the conclusion and discussion section, mention the important results of the research.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 4 Report

1.The author's introduction to the research background is not comprehensive, LS and KF methods and adaptive algorithms are currently widely used GNSS solution methods. Please add.

2.Are the results of several experiments generally representative?

3.Please add a description of whether the experimental environment is representative.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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