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The maturity reached in the development of Unmanned Air Vehicles (UAVs) systems is making them more and more attractive for a vast number of civil missions. Clearly, the introduction of UAVs in the civil airspace requiring practical and effective regulation is one of the most critical issues being currently discussed. As several civil air authorities report in their regulations “Sense and Avoid” or “Detect and Avoid” capabilities are critical to the successful integration of UAV into the civil airspace. One possible approach to achieve this capability, specifically for operations beyond the Line-of-Sight, would be to equip air vehicles with a vision-based system using cameras to monitor the surrounding air space and to classify other air vehicles flying in close proximity. This paper presents an image-based application for the supervised classification of air vehicles.

The design of a longitudinal stability augmentation system (SAS) for an aircraft with reduced tail size in the preliminary design phase is presented. Reducing tail size will reduce drag and weight and result in better fuel consumption, but it will reduce the level of stability. A control law is designed to give the aircraft the same stability level as that with the initial tail size. The feedback gains of the control law is computed with the equivalent stability derivative criteria of and CmαCmq . The paper also gives an overview of classical root locus and pole placement method and demonstrates that equivalent stability derivative criteria is suitable for preliminary aircraft design applications. Moreover, the control laws are also synthesized using robust control LQG/LTR which can be elaborated more in the detail design phase.

This paper presents the conceptual design of a new low-cost measurement system for the determination of pollutant concentrations associated with aircraft operations. The proposed system employs Light Detection and Ranging (LIDAR) and passive electro-optics equipment installed in two non-collocated components. The source component consists of a tuneable small-size and low-cost/weight LIDAR emitter, which can be installed either on airborne or ground-based autonomous vehicles, or in fixed surface installations. The sensor component includes a target surface calibrated for reflectance and passive electro-optics equipment calibrated for radiance, both installed on an adjustable support. The proposed bistatic system determines the column-averaged molecular and aerosol pollutant concentrations along the LIDAR beam by measuring the cumulative absorption and scattering phenomena along the optical slant range.