Disturbance Observer and Depth Enhanced Visual-Inertial Navigation System For Multi-rotor MAVs: An Observability Analysis

This paper proposes a new filtering-based depth enhanced visual internal navigation system (DE-VINS) with external disturbance observation. This filter resolves the drifting and degraded performance of drag force model VINS filters at hovering conditions and during the existence of external disturbances. A theoretical nonlinear observability analysis is performed to verify the filter design. The performance of the proposed DE-VINS is investigated through two sets of numerical simulations using a Matlab simulator and compared against the state-of-the-art drag force VINS filters. The results show improved performance of the DE-VINS in terms of estimation accuracy and consistency at zero-velocity flight (hovering) during the existence of external disturbances while estimating the magnitude and direction of the disturbance force.