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The radar micro-Doppler signature of a target is determined by parts of the target moving or rotating in addition to the main body motion. The relative motion of these parts is characteristic for different classes of targets, e.g. the flapping motion of a bird’s wings versus the spinning of propeller blades. In the present study, the micro-Doppler signature is exploited to discriminate birds and small unmanned aerial vehicles (UAVs). Emphasis is on micro-Doppler features that can be extracted from spectrograms and cepstrograms, enabling the human eye or indeed automatic classification algorithms to make a quick distinction between man-made objects and bio-life. In addition, in case of man-made objects, it is desired to further characterize the type of mini-UAV to aid the threat assessment. Also this characterization is done on the basis of micro-Doppler features.

This paper shows how Unmanned Aerial Vehicles (UAVs) can improve security in major sporting events. Given the increase in violence among sports fans it is important to timely monitor possible conflict locations. A UAV can patrol and remotely monitor the activity at these locations. Such a patrol tour should be repeatedly executed in order to constantly update the available information about the different locations. Besides aiming to find a short tour to efficiently monitor all locations, it is important to take into consideration that the UAV might be redirected from its tour to another location where some abnormal activity is taking place. In this paper we introduce a general binary fractional program which provides a method to find a balance between the tour duration and the ability of the UAV to fly to locations of new conflicts as soon as possible. Using a case study we illustrate the purpose of our model.

This paper shows how Unmanned Aerial Vehicles (UAVs) can improve security in major sporting events. Given the increase in violence among sports fans it is important to timely monitor possible conflict locations. A UAV can patrol and remotely monitor the activity at these locations. Such a patrol tour should be repeatedly executed in order to constantly update the available information about the different locations. Besides aiming to find a short tour to efficiently monitor all locations, it is important to take into consideration that the UAV might be redirected from its tour to another location where some abnormal activity is taking place. In this paper we introduce a general binary fractional program which provides a method to find a balance between the tour duration and the ability of the UAV to fly to locations of new conflicts as soon as possible. Using a case study we illustrate the purpose of our model.