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Article
Peer-Review Record

WiFi Access Points Line-of-Sight Detection for Indoor Positioning Using the Signal Round Trip Time

Remote Sens. 2022, 14(23), 6052; https://doi.org/10.3390/rs14236052
by Xu Feng 1,*, Khuong An Nguyen 1 and Zhiyuan Luo 2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2022, 14(23), 6052; https://doi.org/10.3390/rs14236052
Submission received: 14 October 2022 / Revised: 19 November 2022 / Accepted: 27 November 2022 / Published: 29 November 2022
(This article belongs to the Special Issue Remote Sensing in Urban Positioning and Navigation)

Round 1

Reviewer 1 Report

WiFi Access Points Line-of-Sight Detection Using

The Signal Round Trip Time for Indoor Positioning

 

The authors propose a feature selection algorithm for non-line-of-sight identification of the Wi-Fi Access Points to minimize the challenge arising from attenuated, reflected, blocked, or interfered, and fluctuating and unpredictable signal measurements in Wi-Fi indoor localization systems. They set up experiments and measured their framework performance. The results show significant improvement over the pear methods.

 

They made the dataset that contains WiFi RSS and RTT signal measures and LOS

conditions of each AP for every location publicly available. This is important for future research baseline comparison and replicating their results.

 

I think that the overall work of the authors is very well. However, they need to strengthen their discussion and clarify the following points.

 

1.      In the introduction and related work, I suggest they discuss fingerprinting techniques and how the proposed method can be preferable to fingerprint.

2.      Equation eq(3) and eq(6) there is symbol inconsistency.

 

3.      The conclusion needs to be written better. It is very broad and repeats the result analysis and discussion.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

The authors' proposed a novel feature selection algorithm for non-line-of-sight
identification of the WiFi Access Points is a topic of interest to researchers in related fields, but the paper needs very significant improvement before it can be accepted for publication, as detailed in the following comments.
1- This is a very well structured paper! The relevant parts of the author's work are very clearly described and well organised. It is clear that the author's preliminary work is very well documented. The experiments are adequate and the conclusion of the paper is very well described. No major grammatical errors!
2- I found the introduction to this work to be less descriptive in the paper. As a paper with an excellent structure, I feel that the author should focus on the introduction of the paper. This is because the introduction is an important entry point to an essay and can help the reader to understand more easily what is the background of this thesis study? What is the thesis about? What is the proposed methodology for the study of this thesis? Is its designed methodology sound? What new findings can be made? Is it of academic value? The reader's interest in the thesis depends, to a large extent, on the introduction.
3- It is recommended that in the manuscript, the author should add a vivid simulation or a real picture (or a visual diagram) to describe the intention of the author's work and the points of innovation, etc.
4- There are several questions regarding this work.
a) First of all, all the author's work is based on RSS and RTT of Wi-Fi signals. However, the current mainstream is based on the CSI signal of the Wi-Fi signal for the series of related work[1-2]. We know that CSI has more information about the target and multipath effects than the previous two, so why did the authors choose the former and not the latter? I think it would have been better to base the localisation on the more informative CSI.
b) Secondly, I would like the authors to compare the new manuscript with more recent research findings. The research to be compared could include several aspects, such as CSI... etc.


[1]    Wang, Hao, et al. "Human respiration detection with commodity wifi devices: do user location and body orientation matter?." Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. 2016.

[2]    Yan Wang, Jian Liu, Yingying Chen, Marco Gruteser, Jie Yang, Hongbo Liu . "E-eyes: Device-free Location-oriented Activity Identification Using Fine-grained WiFi Signatures. " MobiCom’14, September 7-11, 2014, Maui, Hawaii, USA

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Good job, but before publishing I recommend double-checking the grammar for errors in the text.

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