Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android Smartphone
The opening access of global navigation satellite system (GNSS) raw data in Android smart devices has led to numerous studies on precise point positioning on mobile phones, among which single-frequency precise point positioning (SF-PPP) has become popular because smartphone-based dual-frequency data...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/23/4894 |
| _version_ | 1797507196778446848 |
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| author | Min Li Zhuo Lei Wenwen Li Kecai Jiang Tengda Huang Jiawei Zheng Qile Zhao |
| author_facet | Min Li Zhuo Lei Wenwen Li Kecai Jiang Tengda Huang Jiawei Zheng Qile Zhao |
| author_sort | Min Li |
| collection | DOAJ |
| description | The opening access of global navigation satellite system (GNSS) raw data in Android smart devices has led to numerous studies on precise point positioning on mobile phones, among which single-frequency precise point positioning (SF-PPP) has become popular because smartphone-based dual-frequency data still suffer from poor observational quality. As the ionospheric delay is a dominant factor in SF-PPP, we first evaluated two SF-PPP approaches with the MGEX (Multi-GNSS Experiment) stations, the Group and Phase Ionospheric Correction (GRAPHIC) approach and the uncombined approach, and then applied them to a Huawei P40 smartphone. For MGEX stations, both approaches achieved less than 0.1 m and 0.2 m accuracy in horizontal and vertical components, respectively. Uncombined SF-PPP manifested a significant decrease in the convergence time by 40.7%, 20.0%, and 13.8% in the east, north, and up components, respectively. For P40 data, the SF-PPP performance was analyzed using data collected with both a built-in antenna and an external geodetic antenna. The P40 data collected with the built-in antenna showed lower carrier-to-noise ratio (C/N0) values, and the pseudorange noise reached 0.67 m, which is about 67% larger than that with a geodetic antenna. Because the P40 pseudorange noise presented a strong correlation with C/N0, a C/N0-dependent weight model was constructed and used for the P40 data with the built-in antenna. The convergence of uncombined SF-PPP approach was faster than the GRAPHIC model for both the internal and external antenna datasets. The root mean square (RMS) errors for the uncombined SF-PPP solutions of P40 with an external antenna were 0.14 m, 0.15 m, and 0.33 m in the east, north, and up directions, respectively. In contrast, the P40 with an embedded antenna could only reach 0.72 m, 0.51 m, and 0.66 m, respectively, indicating severe positioning degradation due to antenna issues. The results indicate that the two SF-PPP models both can achieve sub-meter level positioning accuracy utilizing multi-GNSS single-frequency observations from mobile smartphones. |
| first_indexed | 2024-03-10T04:46:11Z |
| format | Article |
| id | doaj.art-279934c6ec82437695cfc79403ca2444 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T04:46:11Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-279934c6ec82437695cfc79403ca24442023-11-23T02:58:00ZengMDPI AGRemote Sensing2072-42922021-12-011323489410.3390/rs13234894Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android SmartphoneMin Li0Zhuo Lei1Wenwen Li2Kecai Jiang3Tengda Huang4Jiawei Zheng5Qile Zhao6GNSS Research Center, Wuhan University, Wuhan 430079, ChinaGNSS Research Center, Wuhan University, Wuhan 430079, ChinaGNSS Research Center, Wuhan University, Wuhan 430079, ChinaGNSS Research Center, Wuhan University, Wuhan 430079, ChinaGNSS Research Center, Wuhan University, Wuhan 430079, ChinaGNSS Research Center, Wuhan University, Wuhan 430079, ChinaGNSS Research Center, Wuhan University, Wuhan 430079, ChinaThe opening access of global navigation satellite system (GNSS) raw data in Android smart devices has led to numerous studies on precise point positioning on mobile phones, among which single-frequency precise point positioning (SF-PPP) has become popular because smartphone-based dual-frequency data still suffer from poor observational quality. As the ionospheric delay is a dominant factor in SF-PPP, we first evaluated two SF-PPP approaches with the MGEX (Multi-GNSS Experiment) stations, the Group and Phase Ionospheric Correction (GRAPHIC) approach and the uncombined approach, and then applied them to a Huawei P40 smartphone. For MGEX stations, both approaches achieved less than 0.1 m and 0.2 m accuracy in horizontal and vertical components, respectively. Uncombined SF-PPP manifested a significant decrease in the convergence time by 40.7%, 20.0%, and 13.8% in the east, north, and up components, respectively. For P40 data, the SF-PPP performance was analyzed using data collected with both a built-in antenna and an external geodetic antenna. The P40 data collected with the built-in antenna showed lower carrier-to-noise ratio (C/N0) values, and the pseudorange noise reached 0.67 m, which is about 67% larger than that with a geodetic antenna. Because the P40 pseudorange noise presented a strong correlation with C/N0, a C/N0-dependent weight model was constructed and used for the P40 data with the built-in antenna. The convergence of uncombined SF-PPP approach was faster than the GRAPHIC model for both the internal and external antenna datasets. The root mean square (RMS) errors for the uncombined SF-PPP solutions of P40 with an external antenna were 0.14 m, 0.15 m, and 0.33 m in the east, north, and up directions, respectively. In contrast, the P40 with an embedded antenna could only reach 0.72 m, 0.51 m, and 0.66 m, respectively, indicating severe positioning degradation due to antenna issues. The results indicate that the two SF-PPP models both can achieve sub-meter level positioning accuracy utilizing multi-GNSS single-frequency observations from mobile smartphones.https://www.mdpi.com/2072-4292/13/23/4894single-frequency precise point positioningGRAPHIC modeluncombined modelmulti-GNSS systemAndroid smartphone |
| spellingShingle | Min Li Zhuo Lei Wenwen Li Kecai Jiang Tengda Huang Jiawei Zheng Qile Zhao Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android Smartphone Remote Sensing single-frequency precise point positioning GRAPHIC model uncombined model multi-GNSS system Android smartphone |
| title | Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android Smartphone |
| title_full | Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android Smartphone |
| title_fullStr | Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android Smartphone |
| title_full_unstemmed | Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android Smartphone |
| title_short | Performance Evaluation of Single-Frequency Precise Point Positioning and Its Use in the Android Smartphone |
| title_sort | performance evaluation of single frequency precise point positioning and its use in the android smartphone |
| topic | single-frequency precise point positioning GRAPHIC model uncombined model multi-GNSS system Android smartphone |
| url | https://www.mdpi.com/2072-4292/13/23/4894 |
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