Measurement Based Identification of MPCs in an Urban Drone-to-Drone Propagation Scenario

The risk of mid-air collisions between flying drones has to be minimized to the greatest possible extent as it endangers people in the air and on the ground especially when being integrated into dense urban airspace. For a safe and efficient operation drones will need to exchange information in a robust and reliable manner and one essential part will be direct Drone-to-Drone (D2D) communications. Especially, for dense drone scenarios in urban environments a communication system must cope with the specific underlying channel propagation conditions. In previous works, in order to characterize the propagation effects between two moving drones in urban environments, we performed a channel sounding measurement campaign and presented an approach to localize the origin of the measured multipath components (MPCs) for a three-dimensional layout. In this work, we apply this approach on our measured flight scenarios in three different environments in order to identify the MPCs by assigning them to real-world objects. Furthermore, we describe first characteristics for them and show that the measured urban scenario consists of different kinds of components that must be considered in a future D2D channel model.