Reliability and Separability Analysis of Multiple-Fault Detection in Visual Navigation Using Reality-Based 3D Maps

Abstract

Vision-based navigation has been widely accepted as a promising approach to obtain position and orientation information in GNSS-denied environments. However, due to the complexity of such environment, a number of factors such as keypoint mismatch may pose faults for the navigation solution, deteriorating navigation performance. Hence fault detection and isolation is essential for the integrity of the navigation solution. Further, multiple faults assumption is more realistic and general than single-fault assumption. However, the system’s ability to detect and separate potential faults is one critical aspect. In this paper, reliability and separability in both single-fault and multiple-fault case of visual navigation using reality-based 3D maps is comprehensively analyzed through real data from indoor environment. The analysis demonstrates that geometry has an important impact on reliability and separability in both single-fault and multiple-fault scenarios. The better geometry will enhance reliability and separability of such visual navigation system.