Received signal strength indicator-based decentralised control for robust long-range aerial networking using directional antennas

Aerial networking using directional antennas (ANDA) is referred as a promising solution for the networking of unmanned aerial vehicles (UAVs) and for the fast provision of on-demand communication infrastructure to the ground. The cyber constraints on communication channel characteristics and physical constraints on the payload, power, and mobility of UAVs make it challenging to achieve a robust ANDA. In this study, the authors develop a decentralised control algorithm for directional antennas mounted on two moving UAVs to achieve a robust broad-band long-distance communication channel. In particular, the self-alignment of UAV-mounted directional antennas over a long distance is achieved through fusing the Global Positioning System (GPS) and communication channel characteristic measured by received signal strength indicator, using unscented Kalman filter and fuzzy logic. The solution significantly enhances the performance of wireless communication channel in imperfect environment subject to the unavailability of GPS signals and unstable strength of wireless signals. Finally, simulations are performed to validate the decentralised directional antenna control approach.

[1]  Byung-Cheol Min,et al.  Self-orientation of directional antennas, assisted by mobile robots, for receiving the best wireless signal strength , 2012, 2012 IEEE Sensors Applications Symposium Proceedings.

[2]  Randal W. Beard,et al.  GPS-denied relative motion estimation for fixed-wing UAV using the variational pose estimator , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[3]  Seyyed Ali Asghar Shahidian,et al.  Autonomous trajectory control for limited number of aerial platforms in RF source localization , 2015, 2015 3rd RSI International Conference on Robotics and Mechatronics (ICROM).

[4]  Yi Zhou,et al.  A Smooth-Turn Mobility Model for Airborne Networks , 2013, IEEE Trans. Veh. Technol..

[5]  Yi Zhou,et al.  Multi-UAV-Aided Networks: Aerial-Ground Cooperative Vehicular Networking Architecture , 2015, IEEE Vehicular Technology Magazine.

[6]  Ilker Bekmezci,et al.  LODMAC: Location Oriented Directional MAC protocol for FANETs , 2015, Comput. Networks.

[7]  Mi Zhou,et al.  Airborne WiFi networks through directional antennae: An experimental study , 2015, 2015 IEEE Wireless Communications and Networking Conference (WCNC).

[8]  Nicholas Roy,et al.  RANGE–Robust autonomous navigation in GPS‐denied environments , 2011, J. Field Robotics.

[9]  H. T. Kung,et al.  Performance Measurement of 802.11a Wireless Links from UAV to Ground Nodes with Various Antenna Orientations , 2006, Proceedings of 15th International Conference on Computer Communications and Networks.

[10]  Randal W. Beard,et al.  Radar odometry on fixed-wing small unmanned aircraft , 2016, IEEE Transactions on Aerospace and Electronic Systems.

[11]  D. Simon Kalman filtering with state constraints: a survey of linear and nonlinear algorithms , 2010 .

[12]  Ryu Miura,et al.  A dynamic trajectory control algorithm for improving the communication throughput and delay in UAV-aided networks , 2016, IEEE Network.

[13]  Eric T. Matson,et al.  Active Antenna Tracking System with Directional Antennas for Enhancing Wireless Communication Capabilities of a Networked Robotic System , 2016, J. Field Robotics.

[14]  Yan Wan,et al.  UAV-carried Long-distance Wi-Fi Communication Infrastructure , 2016 .

[15]  Denis Pomorski,et al.  GPS/IMU data fusion using multisensor Kalman filtering: introduction of contextual aspects , 2006, Inf. Fusion.

[16]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[17]  A. Krener,et al.  Nonlinear controllability and observability , 1977 .

[18]  Yan Wan,et al.  A Survey and Analysis of Mobility Models for Airborne Networks , 2014, IEEE Communications Surveys & Tutorials.

[19]  Yuanxin Wu,et al.  Unscented Kalman filtering for additive noise case: augmented versus nonaugmented , 2005, IEEE Signal Processing Letters.

[20]  Sally I. McClean,et al.  UAV Position Estimation and Collision Avoidance Using the Extended Kalman Filter , 2013, IEEE Transactions on Vehicular Technology.

[21]  C. W. Chan,et al.  Performance evaluation of UKF-based nonlinear filtering , 2006, Autom..

[22]  Jeffery W. Weston,et al.  Experiment and field demonstration of a 802.11-based ground-UAV mobile ad-hoc network , 2009, MILCOM 2009 - 2009 IEEE Military Communications Conference.