Research on Indoor Localization Algorithm Based on Multi-fusion Bluetooth AOA Using Two-Dimensional DOA Estimation

With the AOA/AOD direction finding technology introduced by Bluetooth Core specification 5.1, Bluetooth has gradually become a research hotspot in the field of indoor positioning with its standard specification protocol, rich application ecology, low cost, low power consumption and other outstanding advantages. Compared with other indoor positioning technologies, Bluetooth indoor positioning has more potential possibilities. However, the current indoor positioning based on Bluetooth AOA is too simple in the core algorithm, resulting in shortcomings such as insufficient real-time performance, low resolution accuracy and poor robustness. In multi-scenario applications, faced with prominent problems such as path loss and complex interference, low universality becomes a significant defect of this method. Therefore, this paper proposes the research of multi-fusion Bluetooth AOA indoor positioning algorithm. Based on the high resolution based on two-dimensional DOA estimation, the short-range advantages of RSSI are integrated for auxiliary optimization, and the intelligence and adaptability of deep learning are combined to realize the expansion of high precision and high performance of multifusion algorithm. The experimental results show that the multi-fusion algorithm has high applicability, can effectively overcome the limitations of single algorithm application, and greatly improve the positioning accuracy and real-time positioning.