融合上下文感知的地标检测辅助WiFi-PDR室内定位

针对当前WiFi-PDR室内定位中存在的WiFi信号不稳定及行人航位推算（PDR）累积误差大的问题，本文提出了一种融合上下文感知的地标检测辅助WiFi-PDR室内定位方法。该方法利用智能手机所能监测到的上下文信息建立用户模型，采用基于卷积神经网络的用户行为感知和基于WiFi-PDR室内定位的粗粒度位置感知，发现隐藏的室内地标信息，并完成用户在地标位置的位置校正，提高定位准确度。该方法在一定程度上降低了WiFi-PDR室内定位的误差，提高了用户室内定位的精度。经试验验证，该室内定位方法的精度相比于传统的WiFi-PDR方法提高了43.62%。

Context-aware landmark detection assists WiFi-PDR indoor localization

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.