A Robust Adaptive Filtering Algorithm for GNSS Single-Frequency RTK of Smartphone
Round 1
Reviewer 1 Report
This paper proposes a single frequency real-time kinematic positioning (RTK) robust adaptive Kalman filtering algorithm. The key models in the proposed algorithm were discussed, including GNSS RTK positioning model, quartile robust model and adaptive model using classification adaptive factor. Through simulation and actual dynamic experiments, it is proved that the algorithm can improve the overall positioning accuracy of mobile phones, and can provide a reference for obtaining continuous and accurate dynamic positioning results. The research of this paper is valuable and has great practical application. However, before the paper is accepted, authors should consider the following questions.
1.Lines 105-111 repeat with lines 112-118.
2.Please explain the meaning of N in formula 1.
3.Please indicate IQR=Q3-Q1 in Figure 1.
4.Lines 278-280 write the mobile phone need to turn off the duty cycle and mechanism. Explain why you need to turn off the duty cycle mechanism?
5.The horizontal line format of the table is different, for example, Table 6 and Table 7.
6.Why are the observation value received by Huawei P40 is interrupted many times and is obviously abnormal during dynamic experiment?
Author Response
请参阅附件。
Author Response File: 
Author Response.docx
Reviewer 2 Report
Thank you for asking me to review this interesting manuscript.
The manuscript presented a robust adaptive RTK positioning algorithm for improving dynamic position estimation. The robust method consisted of using IGG weighting function with adaptive parameters robustly estimated from quartiles. The method consisted also a robust Kalman filter implementation to better support motion changes. The method was quite extensively tested in dynamic test environment with reliable ground truth and it was found to significantly improve the estimation accuracy.
In my opinion, the proposed methods are not particularly new. There are also some deficiencies in describing the test setup, which I have pointed out directly in the attached PDF document. The broad testing campaign is the biggest merit of the manuscript. And the results show that the method is significantly improving the accuracy.
Comments for author File: 
Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Reviewer 3 Report
The single-frequency RTK algorithm with robust filter (not influenced to a large extent by outliers) and its study was presented in the paper. I do not have any general remarks to the quality of the paper but the following specific ones:
1) More discussion on the single frequency RTK and robust estimation should be added in the introduction. The details are given in the commented manuscript.
2) Line 15: IGG is also an abbreviation of other institutes like Vienna Institute of Geodesy and Geophysics. State clearly Chinese.
3) Several references are grouped with authors of one publication like in line 47. State clearly other researchers achievements.
Comments for author File: Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
This paper proposes a single frequency real-time kinematic positioning (RTK) robust adaptive Kalman filtering algorithm. Through simulation and actual dynamic experiments, it is proved that the algorithm can improve the overall positioning accuracy of mobile phones, and can provide a reference for obtaining continuous and accurate dynamic positioning results. In this version, the authors have already replied all the questions I proposed before. I will clarify the comments as well as giving new comments.
1. There are two pictures in Figure 1. Please mark Picture A and picture B and explain the meaning of the two pictures respectively.
2. Please modify the horizontal line format of Table 1, 2, 3, 4, 5, 6, and 9 according to Table 7 and 8.
3. Make sure the figure and figure legends are on the same page, and the table is one the same page as the table legends.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
