Abstract: Aiming at the instability of WiFi signal and the large cumulative error of PDR(pedestrian dead reckoning) in the current WiFi-PDR indoor localization, a context-based landmark detection assisted WiFi-PDR indoor localization method is proposed. This method uses the context information monitored by smart phones to establish a user model, and uses the user behavior perception based on convolutional neural network and coarse-grained location perception based on WiFi-PDR indoor localization to discover the hidden indoor landmark information, and completes the user's location correction at the landmark location to improve the positioning accuracy. This method reduces the indoor localization error of WiFi-PDR to some extent and improves the indoor localization accuracy of users. The experimental results show that the accuracy of the indoor localization method is 43.62% higher than that of the traditional WiFi-PDR method.

Key words: indoor localization, convolutional neural network, context awareness, behavioral perception, location awareness, landmark