AoA Estimation for High Accuracy BLE Positioning

Abstract

Positioning information plays an important role in various indoor services such as route navigation and robot control. Bluetooth Low Energy (BLE), with low power consumption and low cost, are widely installed in mobile devices, and used for indoor localization. Previous methods usually exploit received signal strength indicator (RSSI) to compute position, and the performance is limited. To further improve positioning accuracy, it is desirable to use angle-of-arrival (AoA) information together. However, a BLE receiver has only one receiving module, and cannot receive signals from multiple antennas simultaneously. To solve this problem, Bluetooth 5.1 added the Constant Tone Extension (CTE) to the end of a BLE packet. Then, it is possible for a BLE receiver to switch the antennas and acquire phase information per antenna successively. In this paper, by adjusting parameters related to CTE, we first investigate how to compute AoA by linear regression. Then, we further discuss how to estimate AoA by exploiting the Multiple Single Classification (MUSIC) method. Experimental results show that linear regression can achieve an AoA error of 5.7 degrees, while using MUSIC helps to reduce this error to 2.3 degrees, which is promising for high accuracy positioning.