Optimal Wireless Aerial Sensor Node Positioning for Randomly Deployed Planar Collaborative Beamforming

Recent advancements in low power micro sensors and wireless network technology have enabled a host of new sensor network applications. One such novel application is to perform collaborative beamforming from a wireless sensor network consisting of multirotor aerial vehicles (MAVs). Collaborative beamforming from an airborne wireless sensor network can be an effective means of communication from an unobstructed vantage point. This paper explores the feasibility of such a network. We analyze the beam pattern fluctuations due to position errors from the MAV´s unsteady station keeping. We show that the effects of minor position errors are manageable. Finally, two non-linear constrained optimization techniques for side lobe suppression utilizing the MAVs mobility and station keeping capability are introduced. We demonstrate through simulation that our techniques have similar performance while requiring lower computational cost and complexity compared to the conventional minimum variance distortion less response beamformer.