The Extraction and Characterization of Pseudorange Multipath Based on BDS-3 Multi-Frequency Observations

Abstract

Global Navigation Satellite System (GNSS) observations are subject to various errors during their propagation process. A reasonable correction of these errors can improve the positioning, navigation, and timing (PNT) service capability. The impact of multipaths on pseudorange observations can reach a decimeters or even meters level. However, their mechanism is complex and there is currently no universally accepted high-precision correction model. The correlation between the pseudorange multipaths (MP) of BDS-2 satellites and satellite elevation has been confirmed, while there have been fewer analyses of the MP characteristics for different frequencies of BDS-3 satellites. The broadcasting of multi-frequency observations in BDS-3 should theoretically make the extracted MP more accurate compared to traditional methods. Based on this, in this contribution, a multi-frequency MP extraction algorithm based on the least squares principle is proposed, which can simultaneously eliminate the influence of higher-order ionospheric delay. The analytical expression for only eliminating first-order ionospheric delay is successfully derived. Subsequently, the characteristics of the MPs extracted from different frequency combinations and the impact of combination noise on the extraction accuracy are discussed. The influence of second-order ionospheric delay on the MPs for each frequency under different combination noises, as well as the periodic behavior exhibited in long-term observations of the BDS-3 medium earth orbit (MEO) and inclined geosynchronous orbit (IGSO) satellites, are also analyzed. Finally, the correlations between the MPs of each frequency of BDS satellite and elevation are quantitatively analyzed based on observations from 35 stations. Overall, this work has positive implications for the study of the MP characteristics of BDS-3 and subsequent modeling efforts.

Overbounding Ifree errors based on bayesian Gaussian mixture model for ground-based augmentation system

“…The GMM calculates the accurate observations by means of the Gaussian possibility densities. Every GMM comprises of 𝐾 Gaussian distributions, then every observation 𝑞 have the distributions as numerically presented in (9),…”

“…The space-based augmentation system (SBAS) communicates real-time error correlations through geostationary satellites. This SBAS utilizes a global positioning system (GPS) signal which provides an easy way for SBAS signal to GPS receiver without the substantial modifications [8], [9]. Additionally, SBAS generates truthfulness in data correlation for error bound positions.…”