Experimental Investigation on the Performance of Angle-of-Arrival-based Asset Localization in a Warehouse

Abstract

Accurate asset tracking and indoor localization (IL) is of interest in many applications including IoT sensing, shipping warehouse organization, and indoor navigation. Angle-based IL methods, such as angle-of-arrival (AOA), are known for their excellent accuracy. Moreover, their built-in support in the Bluetooth low energy (BLE) stack enables scalable and straight forward IL implementations. In this investigation, important considerations regarding the localization system parameters, including the number and location of anchor nodes, and tracked assets are explored.