Peer-Review Record
PSO-LSSVR Assisted GPS/INS Positioning in Occlusion Region
Sensors 2019, 19(23), 5256; https://doi.org/10.3390/s19235256
Reviewer 1:
Anonymous
Reviewer 2:
Anonymous
Sensors 2019, 19(23), 5256; https://doi.org/10.3390/s19235256
Submission received: 18 October 2019
/
Revised: 15 November 2019
/
Accepted: 24 November 2019
/
Published: 29 November 2019
(This article belongs to the Section Intelligent Sensors)
Round 1
Reviewer 1 Report
Lack of detailed up-to-date relative work analysis. The paper mentioned 19-dimensional state parameters were considered, but these parameters are not clearly presented in the subsequent derivation formula. In filter anomaly detection processing, what is the value of the confidence level Alpha or how to set the Alpha’s value? The iteration of machine learning and the calculation of multiple particles of particle filter are very time-consuming. The paper should analyze the sample number, particle number and related time complexity. Time index should also be given in the experiments. The experiments are not compared with other localization methods proposed to overcome gps failed problem in occlusion region, but only with different EKF methods.
Author Response
Due to the formula and picture in the reply cannot be displayed in the box. Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Even the well-known acronyms have to be defined: GPS, INS, UD?
Is line 66 correct: “attitude error?”
Lines 65-70 are unclear. Please rewrite them.
Line 98: eq. (5), Please define N(01)
Can you write something related to calculus duration? The results contain the frequency, but not an estimation of the calculus on a specified processor.
Author Response
Due to the formula and picture in the reply cannot be displayed in the box. Please see the attachment.
Author Response File: Author Response.pdf
