1,720,991 research outputs found
Towards a Strategic Deconfliction Service Based on Multi-Objective Path Planning for Low Altitude Airspace
No full textThis paper presents a centralized strategic planning and deconfliction service solution which is able to return conflict free trajectories for Urban Air Mobility applications. The service, specifically tailored for dealing with the free-flight portion of the assumed airspace model is targeted for rotorcraft platforms and for off-line (pre-flight) computation. It is able to handle several types of missions and to deconflict them using the reasonable time to act concept. The latter has been introduced by Corus-XUAM to overcome the first-come first-served criteria and aims at solving deconfliction by sorting the vehicles as a function of their priority and required starting time. Two phases are envisaged by the planner in accordance with the current regulation. The first phase, referred to as strategic, is performed when the user exposes the willing of performing the mission (it can occur also long time before the mission start) and is demanded at finding an optimal trajectory accounting for all the constraints imposed by the urban environment (e.g., fixed obstacles, altitude limits, navigation challenges, risk maps), excluding traffic information. The second phase, i.e., pre-tactical, is carried out a few minutes before the mission starts and aims at deconflicting the strategic estimated trajectory with all the existing traffic. The prototype service has been tested within layered airspace model inspired by recent developments and regulatory guidelines. Two layers (i.e., low and medium) aimed at either goods or people transportation have been taken into account over the city of Naples. Different request densities have been considered. Despite the high number of the request, only a little part (2%) of the lower-level airspace is occupied by the traffic, thus suggesting a greater quantity of vehicles could be accomodated. Conversely in the medium level the airspace capacity is strictly linked to the number of vertiports and their availability
Small Mars Satellite
No full textIl progetto prevede lo studio di una missione di esplorazione di Marte con un piccolo lander in grado di trasportare un drone ad ala rotante sulla superficie di Mart
Decentralized cooperative navigation solution for a swarm of UAVs operating in GNSS degraded environment
No full textThis paper presents a decentralized cooperative navigation algorithm which can prevent the overall state estimation divergence by providing a good estimate of cross-covariance terms also in architectures which envisage fully connected graphs. i.e., all the intra-agents measurements are used to update the state of the formation. The proposed approach assumes each agent can independently use non cooperative measurements to update its state. Conversely when cooperative measurements are available a platform (which is iteratively chosen among the formation) is selected to collect all the cooperative information, perform the update and communicate the updated state and covariance to its fellows. The cooperative process is innovative with respect to the other works in the open literature which either make empiric approximations so that cross-covariances can be overestimated or perform cooperative updates by iterating on pairs chosen among the available platforms, thus not allowing an exact covariance update. The proposed algorithm is tested on a scenario simulating fixed wing aircrafts and assuming ranging measurements as intra-agents’ aid. Other simulated measurements include GNSS, IMU, magnetometer and ranging information with respect to moving landmarks. Results are shown by comparing the performance of the proposed algorithm with the centralized (and thus optimal) architecture. In addition, algorithm working conditions are stressed by considering either platform failure or GNSS measurements and other positioning sources (i.e., moving landmarks) occlusions. The latter condition has been considered to test the behavior of the navigation algorithm when only intra-agents ranging are available to bound the formation’s overall navigation error. Results demonstrate the algorithm to perform similar to centralized solution, by mostly depending on the geometry on which the moving landmarks are placed
Ionosphere-gradient based filtering approach for precise relative navigation in LEO
No full textFormation flying missions require the knowledge of the relative positions of the satellites for formation, maintenance and scientific purposes. In Low Earth Orbit, this task is typically performed by GPS-based navigation filters. However, the final accuracy, especially over long baselines, is strongly affected by the capability of correctly estimating the ionospheric delays. In this paper the performance of a real-time relative positioning filter are improved with the introduction of an ionospheric model capable of representing horizontal ionospheric gradients, referred to as Linear Thin Shell model. This model can be used as an alternative to the most common isotropic ionospheric model. Filter performance is investigated in high and low ionospheric intensity conditions using real flight data. Results show that, in intense ionospheric conditions, positioning accuracy is improved with respect to the case of using an isotropic model
Multi-UAV path planning for autonomous missions in mixed GNSS coverage scenarios
No full textThis paper presents an algorithm for multi-UAV path planning in scenarios with heterogeneous Global Navigation Satellite Systems (GNSS) coverage. In these environments, cooperative strategies can be effectively exploited when flying in GNSS-challenging conditions, e.g., natural/urban canyons, while the different UAVs can fly as independent systems in the absence of navigation issues (i.e., open sky conditions). These different flight environments are taken into account at path planning level, obtaining a distributed multi-UAV system that autonomously reconfigures itself based on mission needs. Path planning, formulated as a vehicle routing problem, aims at defining smooth and flyable polynomial trajectories, whose time of flight is estimated to guarantee coexistence of different UAVs at the same challenging area. The algorithm is tested in a simulation environment directly derived from a real-world 3D scenario, for variable number of UAVs and waypoints. Its solution and computational cost are compared with optimal planning methods. Results show that the computational burden is almost unaffected by the number of UAVs, and it is compatible with near real time implementation even for a relatively large number of waypoints. The provided solution takes full advantage from the available flight resources, reducing mission time for a given set of waypoints and for increasing UAV number
Accurate ionospheric delay model for real-time GPS-based positioning of LEO satellites using horizontal VTEC gradient estimation
No full textIonospheric delays compensation is a mandatory step for precise absolute and relative positioning of Low Earth Orbit Satellites (LEO) by GPS measurements. The most frequently used ionosphere model for real-time GPS-based navigation in LEO is an isotropic model proposed by Lear, which uses the Vertical Total Electron Content (VTEC) above the receiver and a mapping function for TEC evaluation along a given ray path. Based on significant assessed results available for ground-based GPS receivers, we propose the use of a different model relying on the thin shell assumption and a bilinear horizontal variation of the VTEC as a function of latitude and longitude in the shell. It is expected that this model is capable of better describing horizontal gradients in the ionosphere, thus improving ionospheric delay estimation, especially in intense ionospheric conditions. This model is referred to as Linear Thin Shell (LTS). LTS performance in estimating undifferenced and double-differenced ionospheric delays is checked by comparing measured and predicted delays computed using flight data from the GRACE mission. Results show that the LTS always outperforms the isotropic model, especially in case of high solar activity. Moreover, the LTS model provides a higher performance uniformity over a wide range of ionospheric delays, thus ensuring good performance in different conditions. The results obtained demonstrate that the LTS model improves the ionosphere delays estimation accuracy by 20 and 40% for undifferenced and double-differenced delays, respectively. This suggests the LTS model can effectively contribute to improving precision in LEO positioning applications. © 2018, Springer-Verlag GmbH Germany, part of Springer Natur
Multi-UAV formation geometries for cooperative navigation in GNSS-challenging environments
No full textThis paper focuses on the problem of autonomous UAV navigation in GNSS-challenging environments. The proposed approach is based on the idea of supporting the flight
of a ("son") UAV in challenging environments, by means of one or more cooperating ("father") UAVs flying under nominal satellite coverage. Relative sensing and information sharing are the basic cooperation mechanisms. Different sensing architectures are presented in terms of filtering schemes, with the focus set on measurement equations and the relevant covariance matrices. The concept of generalized dilution of precision is introduced as a way to predict the son positioning accuracy
resulting from available GNSS observables and cooperative measurements, and can thus be used to individuate optimal formation geometries and navigation performance bounds. Both numerical simulations in different scenarios, and first results from experimental datasets, demonstrate a good consistency with the achieved navigation accuracy. Experimental data show how proper formation geometries allow cooperative visual measurements to provide meter-level positioning accuracy for
relatively long timeframes, even exploiting only two available pseudoranges
Ground-based Radar Networks for Urban Air Mobility: Design Considerations and Performance Analysis
No full textOptimization of Radar Networks for Airspace Surveillance in UAM and AAM Scenarios
No full textThe paper presents an optimization strategy aimed at determining the optimal locations and orientations of a set of ground-based radar sensors distributed around a region of interest providing airspace surveillance in Urban Air Mobility scenarios. Network geometry definition occurs through an optimization procedure which takes into account altogether maximization of airspace coverage and probability of detection, and minimization of the Cramer-Rao Bound. The approach tries to retrieve optimal locations starting from a large set of candidates which are automatically defined as a function of the area of interest and the scenario topology. Candidates' selection allows efficient a-priori elimination of non-feasible and non-appropriate candidate radar positions. Results of the proposed approach are tested on two different real world scenarios, achieving a coverage of 88.9 per cent for mountainous regions and of 99.2 per cent for almost flat terrain regions when a six elements radar network is considered. The full automation of the entire pipeline allows it to be easily applied to several surveillance scenarios and required performance levels
Conflict Detection Performance of Ground-based Radar Networks for Urban Air Mobility
No full textThe main purpose of this paper is to evaluate the capability of ground-based radar networks of detecting possible conflict threats in urban environment, thus support detect and avoid operations. The analysis is performed in a realistic simulation framework, where urban clutter, several sources of loss and weather conditions (i.e., rain) impact sensing performance. Simulation scenarios are designed taking inspiration from DO-381, and particularized by varying the conflict angle between targets' trajectories and their radar cross-section. A customized tracking algorithm based on the Global Nearest Neighbor (GNN) assignment logic is exploited to process target tracks. Finally, conflict detection is addressed by properly setting time and distance (e.g., vertical and horizontal) thresholds and using as metrics the time to the closest point of approach (TCPA) and the distance at the closest point of approach (DCPA)
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