A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning
The performance requirements for Global Navigation Satellite Systems (GNSS) are becoming more demanding as the range of mission-critical vehicular applications, including the Unmanned Aerial Vehicle (UAV) and ground vehicle-based applications, increases. However, the accuracy and reliability of GNSS...
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| Format: | Article |
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MDPI AG
2021-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/11/2117 |
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| author | Qi Cheng Ping Chen Rui Sun Junhui Wang Yi Mao Washington Yotto Ochieng |
| author_facet | Qi Cheng Ping Chen Rui Sun Junhui Wang Yi Mao Washington Yotto Ochieng |
| author_sort | Qi Cheng |
| collection | DOAJ |
| description | The performance requirements for Global Navigation Satellite Systems (GNSS) are becoming more demanding as the range of mission-critical vehicular applications, including the Unmanned Aerial Vehicle (UAV) and ground vehicle-based applications, increases. However, the accuracy and reliability of GNSS in some environments, such as in urban areas, are often affected by non-line-of-sight (NLOS) signals and multipath effects. It is therefore essential to develop an effective fault detection scheme that can be applied to GNSS observations so as to ensure that the vehicle positioning can be calculated with a high accuracy. In this paper, we propose an online dataset based faulty GNSS measurement detection and exclusion algorithm for vehicle positioning that takes account of the NLOS/multipath affected scenarios. The proposed algorithm enables a real-time online dataset based fault detection and exclusion scheme, which makes it possible to detect multiple faults in different satellites simultaneously and accurately, thereby allowing real-time quality control of GNSS measurements in dynamic urban positioning applications. The algorithm was tested with simulated/artificial step errors in various scenarios in the measured pseudoranges from a dataset acquired from a UAV in an open area. Furthermore, a real-world test was also conducted with a ground-vehicle driving in a dense urban environment to validate the practical efficiency of the proposed algorithm. The UAV based simulation exhibits a fault detection rate of 100% for both single and multi-satellite fault scenarios, with the horizontal positioning accuracy improved to about 1 metre from tens of metres after fault detection and exclusion. The ground vehicle-based real test shows an overall improvement of 26.1% in 3D positioning accuracy in an urban area compared to the traditional least square method. |
| first_indexed | 2024-03-10T10:56:49Z |
| format | Article |
| id | doaj.art-ac8e335e7b8f4012a787bf2b77b5c089 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T10:56:49Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ac8e335e7b8f4012a787bf2b77b5c0892023-11-21T21:48:29ZengMDPI AGRemote Sensing2072-42922021-05-011311211710.3390/rs13112117A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle PositioningQi Cheng0Ping Chen1Rui Sun2Junhui Wang3Yi Mao4Washington Yotto Ochieng5College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaState Key Laboratory of Air Traffic Management System and Technology, Nanjing 210007, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaState Key Laboratory of Air Traffic Management System and Technology, Nanjing 210007, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaThe performance requirements for Global Navigation Satellite Systems (GNSS) are becoming more demanding as the range of mission-critical vehicular applications, including the Unmanned Aerial Vehicle (UAV) and ground vehicle-based applications, increases. However, the accuracy and reliability of GNSS in some environments, such as in urban areas, are often affected by non-line-of-sight (NLOS) signals and multipath effects. It is therefore essential to develop an effective fault detection scheme that can be applied to GNSS observations so as to ensure that the vehicle positioning can be calculated with a high accuracy. In this paper, we propose an online dataset based faulty GNSS measurement detection and exclusion algorithm for vehicle positioning that takes account of the NLOS/multipath affected scenarios. The proposed algorithm enables a real-time online dataset based fault detection and exclusion scheme, which makes it possible to detect multiple faults in different satellites simultaneously and accurately, thereby allowing real-time quality control of GNSS measurements in dynamic urban positioning applications. The algorithm was tested with simulated/artificial step errors in various scenarios in the measured pseudoranges from a dataset acquired from a UAV in an open area. Furthermore, a real-world test was also conducted with a ground-vehicle driving in a dense urban environment to validate the practical efficiency of the proposed algorithm. The UAV based simulation exhibits a fault detection rate of 100% for both single and multi-satellite fault scenarios, with the horizontal positioning accuracy improved to about 1 metre from tens of metres after fault detection and exclusion. The ground vehicle-based real test shows an overall improvement of 26.1% in 3D positioning accuracy in an urban area compared to the traditional least square method.https://www.mdpi.com/2072-4292/13/11/2117GNSSvehicleurban positioningfault detection and exclusion |
| spellingShingle | Qi Cheng Ping Chen Rui Sun Junhui Wang Yi Mao Washington Yotto Ochieng A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning Remote Sensing GNSS vehicle urban positioning fault detection and exclusion |
| title | A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning |
| title_full | A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning |
| title_fullStr | A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning |
| title_full_unstemmed | A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning |
| title_short | A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning |
| title_sort | new faulty gnss measurement detection and exclusion algorithm for urban vehicle positioning |
| topic | GNSS vehicle urban positioning fault detection and exclusion |
| url | https://www.mdpi.com/2072-4292/13/11/2117 |
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