Indoor Localization with a Single Access Point Based on TDoA and AoA

Indoor localization in 5G and the Internet of Things has been paid increasing attentions. Recent advances have demonstrated reasonable localization accuracy that can be provided by using a single access point (AP). Yet, existing single AP localization solutions require frequency hopping or suffer from degraded accuracy performance due to complicated indoor propagation environment. This paper proposes a new single AP indoor localization method based on time difference of arrival (TDoA) and angle of arrival (AoA). We divide multiple antennas into two groups, one group with close distance for AoA estimation and the other group with the farther distance for TDoA estimation. Then, a joint estimation of AoA and ToA is carried by a spatial smoothing-based multiple signal classification (MUSIC) algorithm. Finally, we propose a weighted least squares method based on TDoA and AoA estimations to achieve indoor localization. Simulation results verify the effectiveness of the proposed single AP localization method.