Intelligent identification and mitigation of GNSS multipath errors using adaptive BOCPD

Abstract

Reliable knowledge of the complete navigation states is a key requirement for the mobile mapping and land localization applications. And it is the system integrating strapdown inertial navigation system (SINS) and global navigation satellite system (GNSS) that can seamlessly provide the position, velocity and orientation. In the SINS/GNSS integration, GNSS serves as the accurate reference, however, it is susceptible to the multipath propagations in the dense urban environment where GNSS signals may be reflected by buildings or bridges. When multipath situations occur, the positioning quality of GNSS is dramatically degraded, which also has a negative effect on the stable performance of the integration. Therefore, in order to degrade the negative effect caused by GNSS multipath errors, this paper proposes an intelligent identification and mitigation of GNSS multipath errors method, which employs adaptive bayesian online change point detection (BOCPD) based on the high-precision characteristics of the SINS in the short sampling period. The real tests are conducted, which demonstrate that the proposed approach can effectively identify and mitigate GNSS multipath errors, and then improve the accuracy and reliability of the integration.