Advanced Receiver Autonomous Integrity Monitoring (ARAIM) is an evolution of the currently used aviation-focused Global Navigation Satellite System integrity service, Receiver Autonomous Integrity Monitoring (RAIM). Where RAIM supports only lateral navigation, with its adaptations including multiple frequencies and constellations, and with the use of Integrity Support Messages (ISMs), ARAIM also supports vertical guidance. Although these techniques were designed to serve the aviation community, ARAIM could be used in a wide range of applications, especially safety-critical applications. With further evolutions, ARAIM could also be extended to cover more demanding applications in various sectors. This work reports the outcomes of the study of the applicability of ARAIM for the Unmanned Aerial Vehicle (UAV) sector.

As satellite navigation systems show vulnerabilities in specific circumstances such as urban canyons or jamming and spoofing situations, additional sensors such as cameras may be incorporated on the platform. Despite advancements in the robotics and computer vision community, which have led to increasingly accurate Simultaneous Localization and Mapping (SLAM) positioning solutions, visual navigation has its own vulnerabilities. It therefore remains of critical importance for many applications to study the integrity of fused navigation algorithms and their components, which is done less for SLAM than for satellite navigation. In this paper, a framework for integrity monitoring (IM) of a visual SLAM algorithm is proposed. A sensor-level IM scheme analyses feature reprojection errors. It is demonstrated that, in dynamic environments, multiple hypotheses can be generated from different subsets of extracted features. Additionally, the factor graph-based framework employs a fusion-level IM scheme which deals with these multiple hypotheses and selects the most probable one by calculating the sum of weighted measurement residuals. These concepts are applied to scenarios from real and simulated experiments in order to demonstrate applicability.