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In this paper we present a novel Navigation and Guidance System (NGS) for Unmanned Aerial Vehicles (UAVs) based
on Vision Based Navigation (VBN) and other avionics sensors. The main objective of our research is to design a lowcost
and low-weight/volume NGS capable of providing the required level of performance in all flight phases of modern
small- to medium-size UAVs, with a special focus on automated precision approach and landing, where VBN techniques
can be fully exploited in a multisensory integrated architecture. Various existing techniques for VBN are compared and
the Appearance-based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow
techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and
body rates. Additionally, we address the possible synergies between VBN, Global Navigation Satellite System (GNSS)
and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors and also the use of Aircraft
Dynamics Models (ADMs) to provide additional information suitable to compensate for the shortcomings of VBN
sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the
information provided by the different sensors and to provide estimates of position, velocity and attitude of the platform
in real-time. Two different integrated navigation system architectures are implemented. The first uses VBN at 20 Hz
and GPS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also includes the ADM
(computations performed at 100 Hz) to provide augmentation of the attitude channel. Simulation of these two modes is
performed in a significant portion of the Aerosonde UAV operational flight envelope and performing a variety of
representative manoeuvres (i.e., straight climb, level turning, turning descent and climb, straight descent, etc.).
Simulation of the first integrated navigation system architecture (VBN/GPS/IMU) shows that the integrated system can
reach position, velocity and attitude accuracies compatible with CAT-II precision approach requirements. Simulation of
the second system architecture (VBN/GPS/IMU/ADM) shows promising results since the achieved attitude accuracy is
higher using the ADM/VBS/IMU than using VBS/IMU only. However, due to rapid divergence of the ADM virtual
sensor, there is a need for a frequent re-initialisation of the ADM data module, which is strongly dependent on the UAV
flight dynamics and the specific manoeuvring transitions performed. Finally, the output provided by the VBN and
integrated navigation sensor systems is used to design a flight control system using a hybrid Fuzzy Logic and
Proportional-Integral-Derivative (PID) controller for the Aerosonde UAV.
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