IM-GIV: an effective integrity monitoring scheme for tightly-coupled GNSS/INS/Vision integration based on factor graph optimization

TL;DR

This paper introduces a novel position error bounding method for GNSS/INS/Vision integration using factor graph optimization, enhancing integrity monitoring for safety-critical navigation applications.

Contribution

It develops and validates the first position error bounding formula based on FGO residuals, improving integrity monitoring over traditional Kalman filter methods.

Findings

Accurately bounds position error under various fault conditions

Achieves 100% integrity availability after fault exclusion

Demonstrates effectiveness through field experiments

Abstract

Global Navigation Satellite System/Inertial Navigation System (GNSS/INS)/Vision integration based on factor graph optimization (FGO) has recently attracted extensive attention in navigation and robotics community. Integrity monitoring (IM) capability is required when FGO-based integrated navigation system is used for safety-critical applications. However, traditional researches on IM of integrated navigation system are mostly based on Kalman filter. It is urgent to develop effective IM scheme for FGO-based GNSS/INS/Vision integration. In this contribution, the position error bounding formula to ensure the integrity of the GNSS/INS/Vision integration based on FGO is designed and validated for the first time. It can be calculated by the linearized equations from the residuals of GNSS pseudo-range, IMU pre-integration and visual measurements. The specific position error bounding is given in the case of GNSS, INS and visual measurement faults. Field experiments were conducted to evaluate and validate the performance of the proposed position error bounding. Experimental results demonstrate that the proposed position error bounding for the GNSS/INS/Vision integration based on FGO can correctly fit the position error against different fault modes, and the availability of integrity in six fault modes is 100% after correct and timely fault exclusion.