Effects of the Wind Field on the Synthetic Measurement of the Aerodynamic Angles of an Aerial Vehicle

The estimation of the angle of attack and sideslip angle is of fundamental importance for the situational awareness of an aerial vehicle. Historically, several accidents occurred due to failures of the traditional protruding probes applied to measure these two angles. The MIDAS project aims to design and develop a certifiable Air Data System capable of providing the entire set of Air Data, integrating a synthetic estimation of the aerodynamic angles. All operating conditions shall be taken into account, even those related to atmospheric phenomena. The wind effects (both steady and unsteady) represent a very challenging topic when design a synthetic sensor because of its intrinsic nature. In fact, the airflow surrounding the AC can be affected by several phenomena with a very wide range of characteristics (e.g. speed and direction range) that can be hardly simulated during the design stage. It is clear that the atmosphere condition (both steady and unsteady) can affect this particular kind of sensor, and it must be analysed the error in the presence of the wind. The paper shows the estimation error due to the steady wind field and correction to be applied to previous synthetic sensors design in order to be reliable both in still air and in presence of the wind

Safety Analysis of a Certifiable Air Data System Based on Synthetic Sensors for Flow Angle Estimation

This work deals with the safety analysis of an air data system (ADS) partially based on synthetic sensors. The ADS is designed for the small aircraft transportation (SAT) community and is suitable for future unmanned aerial vehicles and urban air mobility applications. The ADS’s main innovation is based on estimation of the flow angles (angle-of-attack and angle-of-sideslip) using synthetic sensors instead of classical vanes (or sensors), whereas pressure and temperature are directly measured with Pitot and temperature probes. As the air data system is a safety-critical system, safety analyses are performed and the results are compared with the safety objectives required by the aircraft integrator. The present paper introduces the common aeronautical procedures for system safety assessment applied to a safety critical system partially based on synthetic sensors. The mean time between failures of ADS’s sub-parts are estimated on a statistical basis in order to evaluate the failure rate of the ADS’s functions. The proposed safety analysis is also useful in identifying the most critical air data system parts and sub-parts. Possible technological gaps to be filled to achieve the airworthiness safety objectives with nonredundant architectures are also identified

Mobile Ground Station for the Unmanned Elettra-Twin-Flyer Airship

In recent years the development of unmanned platforms has exasperated the concept of design and planning in aeronautics: for unmanned flight, in fact, the aerial segment is no longer the central issue and concepts like mission planning, mission and on board sensor management are becoming more and more critical. The majority of these functionalities have been separated from the aerial segment and transferred to the Ground Station (GS) which is one of the key elements of the Unmanned Aerial System (UAS) together with the Communication Link and the Launch and Recovery Element. Safety requirements are thus transferred to some of the GS components, especially to those which perform critical functions. This has contributed to increase the CS complexity. Regardless of the UAV architecture and overall dimension, in fact, the pilot must be able to operate under the same condition of situation awareness of a correspondent manned aircraft. In this context, advanced vision systems and innovative human-machine interfaces must be designed, to enable the pilot to process the flight data while accomplishing the mission task. This paper presents a technological solutions adopted for the Elettra-Twin-Flyer, a lighter-than-air unmanned platform, developed for civil applications

Nonvisible Satellite Estimation Algorithm for Improved UAV Navigation in Mountainous Regions

This paper presents a very simple and computationally efficient algorithm for the calculation of the occlusion points of a scene, observed from a given point of view. This algorithm is used to calculate, in any point of a control volume, the number of visible satellites and the Dilution Of Precision (DOP). Knowledge of these information is extremely important to reject measurements of non-visible satellites and for the reconstruction of a fictitious Digital Elevation Map (DEM), that envelops all the regions characterized by a number of visible satellites lower than a given threshold. This DEM evolves in time according to the platform motion and satellite dynamics. Because of this time dependency, the Digital Morphing Map (DMM) has been defined. When the DMM is available, it can be used by the path planning algorithm to optimise the platform trajectory in order to avoid regions where the number of visible satellites is dramatically reduced, the DOP value is very high and the risk to receive corrupted measurement is large. In this paper also presents the concept of a Safety Bubble Obstacle Avoidance (SBOA) system. This technique takes advantage from the numerical properties of the covariance matrix defined in the Kalman filtering process. A space and time safety bubble is defined according to the DOP value and is used to automatically determine a minimum fly distance from the surrounding obstacles

Structure Design for the Elettra Twin Flyer Prototype

This paper presents different structural solutions compared under the same manoeuvrability and operativity requirements. The structures to be analysed are chosen from an initial set, selected among many solutions which fulfil the dimensional requirements. The airship, in fact, has to be big enough to accommodate a pre-determined volume of payload, has to accommodate the motors in pre-defined locations to allow a good manoeuvrability while limiting the structural deformations, must be able to house all the systems necessary for its operation and should be able to contain enough volume of helium as to sustain at least the 95 % of the structure weight. To minimize the costs of the structural analysis two configurations has been selected as the most representative of the many configurations proposed: the non-rigid double-hull (Figure 1) and the rigid soap-shape airship (Figure 2). Among the available aeronautical technologies, the aluminium truss and the carbon sandwich structures have been considered for the exoskeleton of the soap-shape airship. On the other hand, the structure of the double-hull is too complex to be realized by standard aluminium components, so only the carbon sandwich solution has been analysed

Sensitivity Analysis of a Neural Network based Avionic System by Simulated Fault and Noise Injection

The application of virtual sensor is widely discussed in literature as a cost effective solution compared to classical physical architectures. RAMS (Reliability, Availability, Maintainability and Safety) performance of the entire avionic system seem to be greatly improved using analytical redundancy. However, commercial applications are still uncommon. A complete analysis of the behavior of these models must be conducted before implementing them as an effective alternative for aircraft sensors. In this paper, a virtual sensor based on neural network called Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) is analyzed through simulation. The model simulates realistic input signals of typical inertial and air data MEMS (Micro Electro-Mechanical Systems) sensors. A procedure to define the background noise model is applied and two different cases are shown. The first considers only the sensor noise whereas the latter uses the same procedure with the operative flight noise. Flight tests have been conducted to measure the disturbances on the inertial and air data sensors. Comparison of the Power Spectral Density function is carried out between operative and background noise. A model for GNSS (Global Navigation Satellite System) receiver, complete with constellation simulator and atmospheric delay evaluation, is also implemented. Eventually, a simple multi-sensor data fusion technique is modeled. Results show good robustness of the Smart-ADAHRS to the sensor faults and a marginal sensitivity to the temperature-related faults. Solution for this kind of degradation is indicated at the end of the paper. Influences of noise on input signals is also discussed

Advantages of Neural Network Based Air Data Estimation for Unmanned Aerial Vehicles

Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility

Innovative airplane ground handling system for green operations

The aim of this work is to develop a new concept of taxiing, in order to reduce the pollution in terms of noise and gas emission and to introduce a higher level of safety during ground operations. In the area close to the airport gates, the airplane ground handlings are currently performed through the airplane engines, which have the task of providing the trust necessary to move the airplane to the runway. Pollutant emissions and the noise level near the gates, however, could be drastically reduced by introducing an innovative autonomous tractor called CHAT (Clean Hydrogen Autonomous Tractor), developed from the standard pushback tractor. The ground operations could be basically modified by extending the time in which the airplane engines are idle and the airplane is towed by the tractors powered by renewable energy