Hybrid TOA/AOA Localization with 1D Angle Estimation in UAV-assisted WSN

Unmanned aerial vehicles (UAVs) are considered as a great solution for a flexible and rapid deployment of wireless sensor networks (WSN) in emergency scenarios. Hybrid time-of-arrival (TOA) and angle-of-arrival (AOA) localization is widely used to estimate agents' positions in WSN. Conventional TOA/AOA localization methods normally require both elevation and azimuth AOA estimations to estimate agents' positions, leading to complicated L-shape antenna arrays and power-thirsty two-dimensional signal processing at the agents. We propose a hybrid TOA/1AOA localization approach which only requires elevation AOA estimations to combine with TOA measurements. A weighted least square algorithm is proposed to solve the non-linear problem. The performance of the proposed method is compared with that of the conventional approach under various scenarios. Simulation results show that, by adjusting different parameters such as transmit power, signal bandwidth, and the number of anchors, the proposed method outperforms the conventional counterpart while significantly reduces the complexity of the agents.