Abstract
In recent years, application services based on indoor locations have become increasingly popular, attracting extensive research attention. Among these application services, indoor location technology based on Wi-Fi signal fingerprints has developed rapidly. However, wireless signal transmission is easily affected by the environment, which will lead to deviations in the fingerprint location of the Wi-Fi signal. To improve the location accuracy and reduce the adverse effects of environmental factors, a method of fingerprint location for Wi-Fi signals assisted by smart phone built-in sensors is proposed, that is, to use the built-in sensors such as the accelerometer and gyroscope to collect data, calculate the user’s track information and track credibility, and combine the track information and signal fingerprint information to establish a comprehensive probability model, perform position matching, and determine the nearest reference point. The experimental results show that compared with the traditional fingerprint location method of Wi-Fi signals, the user trajectory information estimated from the sensor data can be used to effectively overcome the impact of environmental changes and improve the average location accuracy.
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