Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations
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 stabi...
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MDPI AG
2024-11-01
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| author | Mohammed Abou Galala Wu Chen |
| author_facet | Mohammed Abou Galala Wu Chen |
| author_sort | Mohammed Abou Galala |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2c32bee99bd84521804a5b7b395622b7 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-11-01 |
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| spelling | doaj-art-2c32bee99bd84521804a5b7b395622b72025-08-20T01:55:41ZengMDPI AGRemote Sensing2072-42922024-11-011623446310.3390/rs16234463Estimation of Signal Distortion Bias Using Geometry-Free Linear CombinationsMohammed Abou Galala0Wu Chen1Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, ChinaSignal 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.https://www.mdpi.com/2072-4292/16/23/4463precise point positioning (PPP)signal distortion bias (SDB)differential code bias (DCB) |
| spellingShingle | Mohammed Abou Galala Wu Chen Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations Remote Sensing precise point positioning (PPP) signal distortion bias (SDB) differential code bias (DCB) |
| title | Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations |
| title_full | Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations |
| title_fullStr | Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations |
| title_full_unstemmed | Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations |
| title_short | Estimation of Signal Distortion Bias Using Geometry-Free Linear Combinations |
| title_sort | estimation of signal distortion bias using geometry free linear combinations |
| topic | precise point positioning (PPP) signal distortion bias (SDB) differential code bias (DCB) |
| url | https://www.mdpi.com/2072-4292/16/23/4463 |
| work_keys_str_mv | AT mohammedabougalala estimationofsignaldistortionbiasusinggeometryfreelinearcombinations AT wuchen estimationofsignaldistortionbiasusinggeometryfreelinearcombinations |