Identification from Flight Data of the Aerodynamics of an Experimental Re-Entry Vehicle

Post flight data analyses are essential activities in aerospace projects. In particular, there is a specific interest in obtaining vehicle aerodynamic characteristics from flight data, especially for re-entry vehicle, in order to better understand theoretical predictions, to validate wind- tunnel test results and to get more accurate and reliable mathematical models for the purpose of simulation, stability analysis, and control system design and evaluation. Indeed, due to atmospheric re-entry specificity in terms of environment and phenomena, ground based experiments are not fully exhaustive and in-flight experimentation is mandatory. Moreover pre-flight models are usually characterised by wide uncertainty ranges, which should be reduced. These objectives can be reached by performing vehicle’s model identification from flight data

Multi-step strategy for rotorcraft model identification from flight data

The availability of suitable methods for system identification from flight data of rotorcraft models is a key factor to enhance the competitiveness of the rotorcraft industry in the development process of new vehicles. Indeed, reliable simulation models provided by the identification techniques can be used for the design and validation of the vehicle flight control system. It allows minimizing the number of in flight experimental tests and consequently reducing costs and risks related to flight testing. Identification methodologies generally fall into two categories: frequency-domain and time-domain. Each approach has inherent strengths and weaknesses. Much of the published works on rotorcraft identification deals primarily with frequency-domain methods, which work well at mid and high frequencies associated with the dynamics of the vehicle control inputs and the aero-elastic behaviour of the blades. On the other hand, time-domain methods, which are well assessed for the identification of fixed wing aircraft, provide accurate models at the low frequency scale that is related to the vehicle flight mechanics. In this paper a hybrid time-frequency identification approach is described. The identification process was carried out in the framework of a multi-step strategy and a specific methodology was selected to comply with each step objective. The hybrid time-frequency approach allowed exploiting the advantage of both time and frequency methods, maximizing the information content extracted from the flight data and obtaining an identified model applicable in the whole frequency range of interest. Furthermore the multi-step strategy decomposed the complex starting problem in simplified sub-problems, which are easier to be solved. The proposed methodology was applied to simulated data of the UH60 Black Hawk, generated using the FLIGHTLAB multi-body simulation environment. Preliminary results showed the effectiveness of the proposed identification strategy in terms of convergence and capability of extracting from flight data relevant information on the vehicle dynamic behaviour. Future works will be focused on the refinement of the structure of the rotorcraft model used for identification purpose and on the application of the proposed methodology to set of data gathered during actual rotorcraft flight tests

Implementation and Real-Time Validation of a European Remain Well Clear Function for Unmanned Vehicles

The full integration of Remotely Piloted unmanned vehicles into civil airspace requires first and foremost the integration of a traffic Detect and Avoid (DAA) system into the vehicle. The DAA system supports remote pilots in performing their task of remaining Well Clear from other aircraft and avoiding collisions. Several studies related to the design of a Remain Well Clear function have been performed that served as input for the development of technical standards applicable to non-European countries. In this paper, a Remain Well Clear implementation is proposed that, using the results of past international projects, fits European airspace needs and specificities and can be acceptable to both remote pilots and air traffic controllers, with only minimal impact on the standard operating procedures used for manned aircraft. The proposed Remain Well Clear software has been successfully validated through real-time simulations with pilots and controllers in the loop considering traffic encounters and mission scenarios typically found in European airspace. The achieved results highlight the appropriate situational awareness provided by the proposed RWC function and its effective support to the remote pilot in making adequate decisions in conflict solving. Real-time simulation tests showed that, in almost all cases, an RWC maneuver is successfully performed, giving the RP sufficient time to assess the conflict, coordinate with the controller, if needed, and execute the maneuver. The fundamental role of the proposed RWC function has been especially evident in uncontrolled airspace classes where the controller does not provide any separation provision. Moreover, its effectiveness has also been tested in encounters with aircraft flying under visual flight rules in controlled airspace, where the controller is not informed or has less information regarding these aircraft. The results from validation tests imply two key potential safety benefits, namely: the mitigation of performing a collision avoidance maneuver and the prevention of potential conflict while not disrupting the traffic flow with possible further consequences of generating other potentially hazardous situations

dynamic control allocation through kalman filtering

Control Allocation (CA) in aviation is the problem of distributing the commands among the available actuation means, in order to ensure the achievements of the moments requested by the flight control laws. CA plays a key role in fault-tolerant control systems since it gives robust performances and stability also in presence of faults to one or more aircraft actuators. In this study, a new algorithm is proposed for Control Allocation under both static and dynamic constraints. The proposed algorithm aims at overcoming the most common limitations of the existing algorithms, most of which do not account for actuator dynamics (i.e. they compute a control command that might not be compatible with aircraft performance limitations) and rely on iterative methods. The proposed approach does not need an iterative procedure because it rearranges the CA as a state observer problem in which observer states are the actual commands to actuators and observer measurements are the requested moments by the flight control laws. The observer is implemented through a Kalman Filter (KF), with the actuator dynamics as process model and the algebraic relationships between moments and commands as measurement model. The effectiveness of the proposed CA strategy has been shown through a numerical analysis. The numerical simulations showed that the control commands computed by Control Allocation algorithms guarantee moments that match the ones requested by the attitude control laws. This has been verified in nominal conditions (i.e. no actuator faults) but also in faulty ones, where one or more actuators are subject to malfunctioning and, furthermore, in simulations scenarios in which aggressive maneuvers led to the saturation of one or more control surfaces

A Highly Integrated Navigation Unit for On-Orbit Servicing Missions

VINAG (VISION/INS integrated Navigation Assisted by GNSS) is a highly integrated multisensor navigation unit, particularly conceived for On-Orbit Servicing missions. The system is designed to provide all-in-one, on-board real time autonomous absolute navigation as well as pose determination of an uncooperative known object orbiting in LEO (Low Earth Orbit), GEO (GEosynchronous Orbits) and possibly in HEO (Highly Earth Orbit). The system VINAG is under development by a team of Italian companies and universities, co-financed by the Italian Space Agency. Thanks to a tight optimized integration of its subsystems, VINAG is characterized by a low power and mass total budgets and therefore it is suitable for small and very small satellites. In order to provide both 1) absolute orbit and attitude determination and 2) vision-based pose determination, the unit integrates three metrology systems: a Cameras Subsystem (a monocular camera and a Star sensor), an Inertial Measurement Unit (IMU) and a GNSS (Global Navigation Satellite System) receiver. In this paper, we introduce the complete system architecture, the adopted algorithms and then the adopted hardware design solutions. In addition, we describe preliminary numerical simulation results obtained for different orbits from LEO to GEO carried out for the validation phase of VINAG

Unmanned Aircraft Collision Detection and Avoidance for Dealing with Multiple Hazards

Collision Detection and Avoidance is one of the critical technologies for fully allowing Unmanned Aerial Systems to fly in civil airspaces. Current methods evaluate only potential conflicts with other aircraft using specific parameters (e.g., time or distance to closest point of approach) that can only be used for pair-wise encounters, not considering the surrounding environment. The present work proposes a new Collision Detection and Avoidance concept to solve short-term conflicts in scenarios characterized by the simultaneous presence of aircraft and other path constraints (i.e., no-fly zones, bad weather areas and terrain) including geo-fencing limitations. Differently from other open literature methods, the proposed algorithm computes two parameters that synthetically describe the conflict hazard level of a given scenario and its possible evolution, independently from the type and the number of surrounding potential threats. Using such indices, a risk evaluation strategy is proposed that detects hazardous situations and generates an optimal maneuver avoiding potential collisions while not causing secondary conflicts. The effectiveness of the proposed algorithm is demonstrated by means of fast-time and real time simulations in some challenging conflict scenarios that cannot be solved by state of the art Detect and Avoid systems

Differences between URClearED Remain Well Clear and DO-365

In 2017, RTCA published the first release of the Minimum Operational Performance Standards for UAS Detect and Avoid systems, DO-365. In 2019, EUROCAE published the Operational Services and Environment Definition for Detect and Avoid in airspace classes D-G in Europe, and in 2020 RTCA published the first update to DO-365. In 2021 the URClearED project was started to develop the requirements and capabilities for the Remain Well Clear function to be integrated in RPAS flying under instrument flight rules in airspace classes D-G. This paper discusses differences between the URClearED and DO- 365A Remain Well Clear quantification and associated alerting and guidance function requirements. Fast-Time and Real-Time Simulation campaigns have been carried out to motivate and assess the introduced differences