Implementation and Integrity Analysis of an Innovation Detector for GNSS Fault Detection in Graph Optimization based SLAM Tightly Coupled with GNSS

Abstract

Pose information is of great importance for control and navigation. For outdoor applications, Global Navigation Satellite System (GNSS) is a preferable choice because of its ability to supply global consistent positioning results. GNSS has been utilized in a mass of applications such as aviation and autonomous driving. On the other hand, a GNSS receiver is prone to interferences like multipath or spoofing attack. Therefore, a GNSS measurement should pass the authentication before incorporating into the pose estimation. Recently graph optimization based SLAM (Simultaneous Localization and Mapping) system that is tightly coupled with GNSS measurements has been developed to achieve a better positioning performance. However, little existing GNSS fault detection method can be directly adapted to such scheme. In this article we propose an innovation based GNSS fault detector. The proposed detector exploits the prior information derived from the marginalization process of the graph optimization, and can detect abnormalities such as drifts or jumps in GNSS positioning results. Moreover, the theoretically performance of the detector is evaluated in terms of the protection level, and several experiments over public datasets are conducted for performance validation.