This paper analyzes the precise point positioning (PPP) performance based on the BeiDou PPP-B2b service by selecting static and dynamic scenarios to evaluate the positioning performance of the BeiDou PPP-B2b service in different environments. The results show that: 1) The static positioning accuracy of PPP-B2b service in open environments can reach centimeter-level, with the best results over a 7-day experimental period being 2.18 cm east, 1.26 cm north, and 2.74 cm vertical; 2) The dynamic positioning accuracy of PPP-B2b service in open environments can reach decimeter-level, with the dynamic positioning accuracy in the experiment being 0.14 m east, 0.32 m north, and 1.28 m vertical; 3) The loss of packets during the transmission process of PPP-B2b service can lead to the expiration of corrections, making them unusable. In static positioning scenarios under open environments, the longest time to restore precise point positioning after an interruption is 16 seconds. In complex environments, the interruption of PPP-B2b service is more severe, leading to long periods where the orbit cannot be restored.
To boost the precision positioning accuracy of the global navigation satellite system (GNSS) and effectively analyze the position information of GNSS, a precision positioning method based on BeiDou Navigation Satellite System/Global Positioning System (BDS/GPS) fusion is proposed. The proposed method utilizes a unified method for spatio-temporal references to adjust the time synchronization between the BDS and GPS, and a precise positioning mathematical model of GNSS based on BDS/GPS fusion is constructed in this paper. The tropospheric delay and ionospheric delay are corrected respectively through the Saastamoinen model and the ionosphere-free linear combination model, and the Earth’s rotation errors are corrected in the earth-fixed coordinate system. By employing Kalman filtering, the mathematical model problem of precise positioning is transformed into a linear problem, and the three-dimensional coordinate fixed solution of the model is solved to achieve precise positioning of the GNSS. The experimental results validate the high reliability of the proposed method for precision positioning. The root mean square (RMS) values in the east-west (E) direction, elevation (U) direction, and north-south (N) direction are 4.60 cm, 3.97 cm, and 13.77 cm, respectively, and the RMS value in three-dimensional positioning is 15.60 cm. It boasts a strong positioning ability and is available to increase the number of visible satellites. By appropriately adjusting the space satellite structure, it is possible to achieve further enhancements in precision positioning accuracy.
To achieve accurate detection and compensation of gross errors, and improve the accuracy of target positioning and tracking, a multi-dimensional gross error positioning method for Global Navigation Satellite System (GNSS) based on Unscented Kalman Filter (UKF) algorithm is proposed. The data measured by GNSS is then subjected to singular spectrum analysis, which enables the decomposition of the data into its constituent components. Through this analysis, significant features of the data measured by GNSS are extracted, allowing for the subsequent reconstruction. By comparing it with the original measurement data to determine its residual sequence, the cross-validation method is utilized to determine the optimal window length and main component fraction parameters. According to the Interquartile Range (IQR) criterion, the detection of gross errors in the data measured by GNSS is achieved, and different types of gross errors are compensated using the UKF algorithm to achieve multi-dimensional gross error positioning. The experimental results show that the optimal window length and main component fraction parameters are 5 and 800 respectively. The effective signal decomposed by this method is consistent with the original measurement data, and the residual signal trend is stable. All gross errors can be detected and compensated, and the deviation between the positioning trajectory and the actual target motion trajectory is small.
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