In this article, an on-line guidance strategy for terminal area energy management phase of a re-entry flight is proposed. In order to fulfil the objectives of this flight phase, the algorithm continuously performs long- and short-term on-line trajectory generation, also accounting for the most relevant vehicle and trajectory constraints. Long-term guidance computes a reference trajectory which minimizes the distance from the final target. Short-term guidance generates the control commands by computing a trajectory that minimizes the displacement from the reference one, thus compensating for the errors due to the environmental disturbances and to the uncertainties of the vehicle model. In the proposed guidance strategy, the main vehicle performance constraints are appropriately accounted for, thus guaranteeing adaptivity in the failure situations where the manoeuvring capabilities are reduced. The proposed guidance strategy has been developed in the framework of the unmanned space vehicle program of the Italian Aerospace Research Centre for the execution of Dropped Transonic Flight Test second mission. In this article, the algorithm performances and robustness to the vehicle initial state have been assessed through a preliminary Monte Carlo analysis. Furthermore, several simulations with bank angle and angle of attack limitations have shown the effectiveness of the algorithm in the presence of reduced manoeuvring capabilities.

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.

This paper describes the guidance, navigation and control challenges posed by the Unmanned Space Vehicles Program. Within the framework of this program the Italian Aerospace Research Center has conceived several advanced GN&C technologies useful in the Terminal Area Energy Management phase of a re-entry flight pattern. These technologies were flight tested during the first two dropped transonic flight tests (DTFT1 and DTFT2) of the program. More specifically, this paper will present the design of the adaptive guidance algorithms developed to accomplish the mission objectives of the DTFT2 flight test. Flight results will be shown in order to state the performance of the guidance strategy putting in evidence, where possible, its most promising aspects for future TAEM applications