Complexity Reduction for Hybrid TOA/AOA Localization in UAV-Assisted WSNs

Unmanned aerial vehicles (UAVs)-assisted wireless sensor networks (WSNs) have tremendous potential applications due to their flexibility and rapid deployment. Hybrid time-of-arrival (TOA) and angle-of-arrival (AOA) localization techniques are commonly used due to their high accuracy. Conventional TOA/AOA localization algorithms require both zenith and azimuth angle estimations at each agent. Since a zenith-and-azimuth AOA estimation requires an L-shape antenna array and complicated two-dimensional signal processing, conventional TOA/AOA algorithms lead to both hardware and computational complexity and high power consumption at each agent. This paper proposes a hybrid TOA/AOA localization algorithm, named $T1A_{a}$ , to reduce the agents' complexity. $T1A_{a}$ only combines TOA-ranging with the azimuth angle estimation. Thereby, agents only require a one-dimensional antenna array, less complicated signal processing, and thus lower power consumption. Such improvements are important for power-limited WSNs and Internet-of-Things (IoT) systems. Simulations are conducted to prove that the proposed $T1A_{a}$ technique can achieve similar performance as conventional TOA/AOA methods, while significantly simplifying agents' complexity.