Research on Indoor Localization Method Based on Smartphone WiFi-Sound Sensor Fusion

Over the past few years, indoor positioning technology has advanced significantly, allowing researchers to determine a user's location using sensor data generated by smartphones. However, single-sensor localization techniques exhibit poor accuracy and stability. To address this issue, a fusion localization scheme based on the K-means clustering algorithm at the decision level has been employed. By utilizing the WiFi sensor and sound sensor within the smartphone, designed experiments are conducted and compared with a single algorithm to evaluate the localization performance of the fusion approach. The experimental results demonstrate that the fusion algorithm exhibits higher localization accuracy compared to single-sensor localization techniques.