Iterative NDA Positioning Using Angle-of-Arrival Measurements for IoT Sensor Networks

Various positioning techniques have been developed to localize Internet-of-Things (IoT) devices accurately. Because IoT communications are often narrowband, efficient localization can be achieved by deducing the device position from the estimated signal Angle-of-Arrival (AOA) at multiple arrays of antennas. It has recently been shown that significant accuracy gains can further be obtained by iterating between the AOA estimation and multi-lateration steps. However, the existing method relies on the knowledge of the transmitted signal (Data-Aided (DA) estimation) which makes it impractical for narrowband communications where the preamble is short. Non-Data-Aided (NDA) estimation is recommended to improve the positioning accuracy for low capacity IoT sensors. This paper proposes an NDA iterative (NDA-It) algorithm using AOA measurements to determine the position of an IoT sensor. Simulation results show that the proposed algorithm significantly outperforms the DA-It in a Bluetooth Low Energy (BLE) context because it can use a much higher number of samples (snapshots); however, it needs more iterations to converge. The computational complexity analysis proves the competitiveness of the proposed NDA-It. The performance of the algorithms is further investigated in multipath and Non-Line-of-Sight (NLOS) propagation environments. Finally, an experimental setup is built to validate the performance of the proposed algorithms.