Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Aeronautical and Aviation Engineering | en_US |
| dc.contributor.advisor | Wen, Weisong (AAE) | en_US |
| dc.creator | Zhong, Yihan | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/14629 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Outlier awareness and mitigation for GNSS/INS integrated systems for post-processing applications | en_US |
| dcterms.abstract | The Global Navigation Satellite System (GNSS) post-processing applications hold a pivotal position in modern smart cities. Post-processing GNSS technology has been widely applied in applications such as structural health monitoring and pedestrian motion health in open-sky environments. However, GNSS signals are affected by multipath effects and non-line-of-sight received signals under high-rise buildings in urban areas. The positioning results can differ greatly from the real position, and the positioning error can reach tens of meters. To explore better positioning results in urban environments, in this thesis, we develop and publish several new methods to improve the positioning accuracy of navigation using low-cost sensors in urban areas. First, we integrate GNSS and inertial measurement unit (IMU) in smartphones to provide more robust results for smoothing pedestrian trajectories in urban areas. The post-processing results show that our proposed method can provide better positioning results by integrating the IMU from smartphones into the novel factor graph optimization (FGO) framework. Secondly, urban areas typically have pre-built 2D maps where vehicles and pedestrians are navigated within designated lanes or walkways. Considering this constraint, we proposed a GNSS/Map integration with FGO to achieve better positioning performance for urban navigation with multi-epoch map constraints. Crucially, it was observed that the precision of the map serves as a limiting factor for the reliability of the positioning outcome. However, the accuracy of the map can also be affected by the absolute positioning provided by the mapping algorithm. Existing mapping algorithms require extremely expensive hardware, and to overcome the high-cost drawback, we propose an algorithm based on a Micro-Electro-Mechanical Systems (MEMS) IMU and a low-cost GNSS receiver to provide reliable lane-level localization in urban canyons. This cost-effective GNSS/IMU post-processing system achieves an accuracy of approximately 20 centimeters in normal urban environments when utilizing the FGO framework. Furthermore, it demonstrates an approximate 50% improvement in accuracy within highly obstructed urban areas. All the methods have been tested in real-world data. In the future, we want to further investigate collaborative positioning based on multi-source messages, to achieve high-accuracy urban positioning. | en_US |
| dcterms.extent | 131 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2026 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.accessRights | open access | en_US |
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