Aircraft Dynamics Model Augmentation for RPAS Navigation and Guidance

Abstract

An Aircraft Dynamics Model (ADM) augmentation scheme for Remotely Piloted Aircraft System (RPAS) navigation and guidance is presented. The proposed ADM virtual sensor is employed in the RPAS navigation system to enhance continuity and accuracy of positioning data in case of Global Navigation Satellite System (GNSS) data degradations/losses, and to improve attitude estimation by vision based sensors and Micro-Electromechanical System Inertial Measurement Unit (MEMS-IMU) sensors. The ADM virtual sensor is essentially a knowledge-based module that predicts RPAS flight dynamics (aircraft trajectory and attitude motion) by employing a rigid body 6-Degree of Freedom (6-DoF) model. Two possible schemes are studied for integration of the ADM module in the aircraft navigation system employing an Extended Kalman Filter (EKF) and an Unscented Kalman Filter (UKF). Additionally, the synergy between the navigation systems and an Avionics-Based Integrity Augmentation (ABIA) module is examined and a sensor-switching framework is proposed to maintain the Required Navigation Performance (RNP) in the event of single and multiple sensor degradations. The ADM performance is assessed through simulation of an RPAS in representative fight operations. Sensitivity analysis of the errors caused by perturbations in the input parameters of the aircraft dynamics is performed to demonstrate the robustness of the proposed approach. Results confirm that the ADM virtual sensor provides improved performance in terms of data accuracy/continuity, and an extension of solution validity time, especially when pre-filtered and employed in conjunction with a UKF.