Sudden Obstacle Appearance Detection by Analyzing Flow Field Vector for Small-Sized UAV

Achieving a reliable obstacle detection and avoidance system that can provide an effective safe avoidance path for small unmanned aerial vehicle (UAV) is very challenging due to its physical size and weight constraints. Prior works tend to employ the vision based-sensor as the main detection sensor but resulting to high dependency on texture appearance while not having a distance sensing capabilities. The previous system only focused on the detection of the static frontal obstacle without observing the environment which may have moving obstacles. On the other hand, most of the wide spectrum range sensors are heavy and expensive hence not suitable for small UAV. In this work, integration of different based sensors was proposed for a small UAV in detecting unpredictable obstacle appearance situation. The detection of the obstacle is accomplished by analysing the flow field vectors in the image frames sequence. The proposed system was evaluated by conducting the experiments in a real environment which consisted of different configuration of the obstacles. The results from the experiment show that the success rate for detecting unpredictable obstacle appearance is high which is 70% and above. Even though some of the introduced obstacles are considered to have poor texture appearances on their surface, the proposed obstacle detection system was still able to detect the correct appearance movement of the obstacles by detecting the edges.

Variation in the Polarization Loss Factor in an Unmanned Aerial Vehicle Jamming Link Due to the Attitude Change

A method to analyze the variation of the jamming power received by an unmanned aerial vehicle (UAV) receiver according to the change in the attitude of the small UAV is presented. The main interest of the study is in the variation of the polarization loss factor (PLF) in the UAV jamming link due to attitude change, which may be caused by the wind or intended movement. The attitude change is modeled by a combination of three successive rotations using roll, pitch, and yaw, which are defined as UAV rotations. The proposed method is applied to a jamming link, where a small UAV with an omnidirectional antenna is jammed by a jammer antenna on the ground. The method is applied to a plane ground and over a simulated terrain. The variation of the PLF according to the change of UAV attitude may be higher than the generally expected PLF at locations where the height difference between the UAV and the jammer is large, and near the locations where the jammer is located close to the vertical plane containing the rotation axis when the attitude change is represented by one rotation.