Improved classification robust Kalman filtering method for precise point positioning

• Autorzy: Zhang Qieqie , Zhao Long , Zhou Jianhua

Identyfikatory

DOI

10.24425/mms.2019.128354

• Języki publikacji: EN

Abstrakty

EN

The accuracy and reliability of Kalman filter are easily affected by the gross errors in observations. Although robust Kalman filter based on equivalent weight function models can reduce the impact of gross errors on filtering results, the conventional equivalent weight function models are more suitable for the observations with the same noise level. For Precise Point Positioning (PPP) with multiple types of observations that have different measuring accuracy and noise levels, the filtering results obtained with conventional robust equivalent weight function models are not the best ones. For this problem, a classification robust equivalent weight function model based on the t-inspection statistics is proposed, which has better performance than the conventional equivalent weight function models in the case of no more than one gross error in a certain type of observations. However, in the case of multiple gross errors in a certain type of observations, the performance of the conventional robust Kalman filter based on the two kinds of equivalent weight function models are barely satisfactory due to the interaction between gross errors. To address this problem, an improved classification robust Kalman filtering method is further proposed in this paper. To verify and evaluate the performance of the proposed method, simulation tests were carried out based on the GPS/BDS data and their results were compared with those obtained with the conventional robust Kalman filtering method. The results show that the improved classification robust Kalman filtering method can effectively reduce the impact of multiple gross errors on the positioning results and significantly improve the positioning accuracy and reliability of PPP.

Słowa kluczowe

EN

Kalman filter; classification robust; equivalent weight function; precise point positioning

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2019
• Tom: Vol. 26, nr 2
• Strony: 267--281
• Opis fizyczny: Bibliogr. 26 poz., rys., tab., wykr., wzory

Twórcy

autor

Zhang Qieqie

• Beihang University, School of Automation Science and Electrical Engineering, Beijing, China
• Beihang University, Digital Navigation Center, Beijing, China

autor

Zhao Long

• Beihang University, School of Automation Science and Electrical Engineering, Beijing, China
• Beihang University, Digital Navigation Center, Beijing, China

autor

Zhou Jianhua

• Beihang University, School of Automation Science and Electrical Engineering, Beijing, China
• Beijing Satellites Navigation Center, Beijing, China

Bibliografia

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Uwagi

EN

1. This project was supported by the National Natural Science Foundation of China (Grants No. 41874034, 41574024 ), the National Science and Technology Major Project of the National Key R&D Program of China (Grant No.2016YFB0502102), the Beijing Natural Science Foundation (Grant No. 4162035), and the Aeronautical Science Foundation of China (Grant No. 2016ZC51024), and the Academic Excellence Foundation of BUAA for PhD Students.

PL

2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).