Multimodal Fusion Indoor Positioning Method for Smartphones

The capacity of smartphones to provide high-precision indoor positioning is an increasingly important application of these devices. Nevertheless, in complex indoor environments, it is challenging to achieve high-precision real-time mobile phone positioning through the use of a single sensor. This paper presents an analysis of the error sources and performance bottlenecks associated with smartphone indoor positioning and outlines the design of a multimodal fusion positioning method. Firstly, initial coarse positioning of the mobile phone is determined at the base station by estimating the angle of arrival (AOA) of the Bluetooth signal broadcast by the mobile phone. Secondly, in the region of coarse positioning, the time difference of arrival (TDOA) of the acoustic signals transmitted from the base station to the mobile phone is combined based on an improved indoor signal propagation model and a geometric dilution of precision (GDOP) factor. Finally, the optimal TDOA set is selected, and the weights of the two sensors are adjusted by updating the GDOP value of the device's current position in real time. Simulation results demonstrate that the proposed multimodal fusion method enhances the efficiency of position computation by 18.7% in comparison to the single-sensor positioning method.