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A 'no-flow-sensor' wind estimation algorithm for Unmanned Aerial Systems (UAS) is presented. It is based on ground speed and flight path azimuth information from the autopilot's GPS system. The algorithm has been tested with the help of the simulation option in the Paparazzi autopilot software using artificial wind profiles. The retrieval accuracy of the predefined profiles by the wind algorithm and its sensitivity to vertical aircraft velocity, diameter of the helical flight pattern and different data sampling methods have been investigated. The algorithm with a correspondingly optimized set of parameters is then applied to various scientific flight missions under real wind conditions performed by the UAS SUMO (Small Unmanned Meteorological Observer). The SUMO wind profiles are compared to measurements of conventional atmospheric profiling systems as radiosondes and piloted balloons. In general, the presented 'noflow-sensor' wind estimation method performs well in most atmospheric situations and is now operationally used in the post-processing routine for wind profile determination from SUMO measurements.

The aim of Air Traffic Flow Management (ATFM) is to enhance the capacity of the airspace while satisfying Air Traffic Control constraints and airlines requests to optimize their operating costs. This paper presents a design of a new route network that tries to optimize these criteria. The basic idea is to consider direct routes only and vertically separate intersecting ones by allocating distinct flight levels, thus leading to a graph coloring problem. This problem is solved using constraint programming after having found large cliques with a greedy algorithm. These cliques are used to post global constraints and guide the search strategy. With an implementation using FaCiLe, our Functional Constraint Library, optimality is achieved for all instances except the largest one, while the corresponding number of flight levels could fit in the current airspace structure. This graph coloring technique has also been tested on various benchmarks, featuring good results on real-life instances, which systematically appear to contain large cliques.

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A conceptual design and performance analysis method (Long Endurance Conceptual Design Program) for long-endurance mini-micro UAVs is presented. Recent long endurance oriented results and achievements are looked through for possible usage for mini-micro scale. A real mission is also explained, whose objective is to accomplish a 200 km straight line flight autonomously with the smallest electric platform possible. Design phases of the platform by using the presented method, flight tests and comparison of the results are included. On the following section a design study for long-endurance MAVs using a hybrid energy system combining solar energy and Lithium batteries and the effect of size and cruise speed are investigated. We demonstrate that under a certain size, the use of solar energy becomes not useful at all. We conclude with the study of a candidate design for EMAV09 Endurance Mission in the light of the rules and scoring of the mission.