A Robust Adaptive Filtering Algorithm for PPP/INS Tightly Coupled Integration with Consideration of Satellite Number Variations
The Precise Point Positioning/Inertial Navigation System (PPP/INS) tightly coupled system, as a high-precision positioning method, is widely used in urban environments. In response to the problems in traditional methods, such as fixed thresholds that neglect the interference of new observations on t...
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| Vydané v: | International Conference on Industrial Mechatronics and Automation (Online) s. 1104 - 1109 |
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| Hlavní autori: | , , , |
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IEEE
03.08.2025
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| ISSN: | 2152-744X |
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| Abstract | The Precise Point Positioning/Inertial Navigation System (PPP/INS) tightly coupled system, as a high-precision positioning method, is widely used in urban environments. In response to the problems in traditional methods, such as fixed thresholds that neglect the interference of new observations on the covariance, and the failure of the satellite number variation mechanism to suppress fluctuations in observation quality, which lead to increased positioning errors, this paper proposes a robust adaptive Kalman filter. First, abnormal observations are suppressed based on a prediction residual threshold. When the residual does not exceed the threshold, satellite number variation detection is performed, and the state noise covariance of the new observations is dynamically adjusted, thus avoiding filter misalignment caused by an excessively large initial covariance. To verify the performance of the algorithm, a vehicle-mounted dynamic experiment was designed, and three filtering schemes were compared. The experiment used real measured data from urban roads, and the results show that, compared to traditional filtering, the two-stage robust adaptive filtering algorithm significantly improves positioning accuracy. Furthermore, in scenarios with frequent satellite number changes, the two-stage robust adaptive filtering demonstrated stronger stability and adaptability. |
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| AbstractList | The Precise Point Positioning/Inertial Navigation System (PPP/INS) tightly coupled system, as a high-precision positioning method, is widely used in urban environments. In response to the problems in traditional methods, such as fixed thresholds that neglect the interference of new observations on the covariance, and the failure of the satellite number variation mechanism to suppress fluctuations in observation quality, which lead to increased positioning errors, this paper proposes a robust adaptive Kalman filter. First, abnormal observations are suppressed based on a prediction residual threshold. When the residual does not exceed the threshold, satellite number variation detection is performed, and the state noise covariance of the new observations is dynamically adjusted, thus avoiding filter misalignment caused by an excessively large initial covariance. To verify the performance of the algorithm, a vehicle-mounted dynamic experiment was designed, and three filtering schemes were compared. The experiment used real measured data from urban roads, and the results show that, compared to traditional filtering, the two-stage robust adaptive filtering algorithm significantly improves positioning accuracy. Furthermore, in scenarios with frequent satellite number changes, the two-stage robust adaptive filtering demonstrated stronger stability and adaptability. |
| Author | Shi, Jinjian Wang, Puxi Yang, Fuxin Lu, Siting |
| Author_xml | – sequence: 1 givenname: Puxi surname: Wang fullname: Wang, Puxi email: 2646104776@qq.com organization: College of Intelligent Systems Science and Engineering, Harbin Engineering University,Harbin,China – sequence: 2 givenname: Siting surname: Lu fullname: Lu, Siting email: Crisdeer@sina.com organization: Southampton Ocean Engineering Joint Institute, Harbin Engineering University,Harbin,China – sequence: 3 givenname: Jinjian surname: Shi fullname: Shi, Jinjian email: linxi@hrbeu.edu.cn organization: College of Intelligent Systems Science and Engineering, Harbin Engineering University,Harbin,China – sequence: 4 givenname: Fuxin surname: Yang fullname: Yang, Fuxin email: yangfuxin@hrbeu.edu.cn organization: College of Intelligent Systems Science and Engineering, Harbin Engineering University,Harbin,China |
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| Snippet | The Precise Point Positioning/Inertial Navigation System (PPP/INS) tightly coupled system, as a high-precision positioning method, is widely used in urban... |
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| SubjectTerms | Accuracy adaptive filtering Filtering Filtering algorithms Fluctuations Heuristic algorithms Kalman filtering Kalman filters Noise PPP/INS tight coupling satellite number variation detection Satellites Urban areas Vehicle dynamics |
| Title | A Robust Adaptive Filtering Algorithm for PPP/INS Tightly Coupled Integration with Consideration of Satellite Number Variations |
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