Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/112841
PIRA download icon_1.1View/Download Full Text
Title: Estimation of signal distortion bias using geometry-free linear combinations
Authors: Galala, MA 
Chen, W 
Issue Date: Dec-2024
Source: Remote sensing, Dec. 2024, v. 16, no. 23, 4463
Abstract: Signal distortion bias (SDB) in Global Navigation Satellite System (GNSS) data processing, defined as the time difference between the distorted chip and the ideal rectangular chip, leads to systematic biases in pseudoranges, affecting satellite and receiver differential code biases (DCBs). The stability of SDBs, allowing them to be treated as constant values, highlights the importance of investigating both their stability and estimation accuracy. Two different methods are used to estimate SDBs: (1) the hybrid method and (2) the geometry-free method. Data from approximately 430 stations, spanning the entire year of 2021, were analyzed to evaluate the estimation accuracy and the short-term and long-term stability of GPS SDBs. The analysis focused on two code signals: C1C (L1 Coarse/Acquisition) and C2W (L2 P(Y)). The results show that the short-term and long-term stability of GPS C1C and C2W SDBs is comparable for both methods, with only minor variations between them. Additionally, one month of data were used to validate the accuracy of estimated SDBs across different receiver groups. The results demonstrate that geometry-free SDBs provide stable satellite DCB estimates with an average bias below 0.15 ns and minimal residual biases, while hybrid SDBs provide satellite DCB estimates with an average bias below 0.20 ns. Overall, the comparison underscores the superior performance of geometry-free SDBs in achieving consistent satellite DCB estimates.
Keywords: Differential code bias (DCB)
Precise point positioning (PPP)
Signal distortion bias (SDB)
Publisher: MDPI AG
Journal: Remote sensing 
EISSN: 2072-4292
DOI: 10.3390/rs16234463
Rights: Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Abou Galala, M., & Chen, W. (2024). Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations. Remote Sensing, 16(23), 4463 is available at https://doi.org/10.3390/rs16234463.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
remotesensing-16-04463-v2.pdf8.9 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.