Positioning of aircraft relative to unknown runway with delayed image data, airdata and inertial measurement fusion

This work addresses the challenge of providing precise runway-relative position, velocity and orientation reference to a landing aircraft based on monocular camera low-cost inertial sensor data complemented by barometric readings. GPS information is excluded from this set because it intended use developed estimator for Instrumental Landing System fault detection. The characteristic size runway assumed be unknown estimated run-time after verifying global observability nonlinear system. delay caused image processing dealt with delayed-Error-State Kalman Filter (ESKF). algorithm considers dynamic propagation between acquisition application forward in time thus does not appear system dynamics. first evaluation done ideal simulated verify applicability delayed-ESKF its flawless implementation. Then more realistic biases noise considered closer performance bias estimation precision. Finally, tested real flight collected VISION EU H2020 research project. Estimation results are compared SBAS-based Airbus precision tolerances showing satisfactory performance. methodological contribution paper unique combination existing methods ideas leading new solution proven satisfactorily even data.