Multimodal Algorithm Based on Particle Filter for Indoor Localization with Smartphones

摘要

Location-based service is one of the most important demand in ubiquitous computing scenarios. While build-in sensors on smartphones can be used to provide location information for terminals. This paper presents a particle filter, dead reckoning, WIFI based multimodal algorithm for indoor localization with smartphones, and propose a system so called ICTIPS. ICTIPS make use of WIFI signal strength measurements, accelerometer, magnetometer and gyroscope on smartphones, as well as map information, offering high tracking accuracy and efficiency. In particular, we compare different weight update strategies for particle filter framework and similarity functions for magnetic matching progress to understand the impact on accuracy and efficiency of the positioning system. In our real office environment, ICTIPS is evaluated with high quality ground truth, which provide service with an average tracking error around 2 meters.