智能手机室内定位在位置服务、公共安全和智慧城市等领域存在重大应用需求，例如，行人导航、安全监控与预警、应急救援与管理、疫情位置追踪等。建筑结构、室内场景及手机使用模式的复杂性，用户和信号的多样性，对室内定位方法的精度和适用性提出了更高要求，由二维扩展至三维的智能手机自适应高精度定位既是当前室内定位的发展趋势，也是一大挑战。本项目紧密围绕智能手机室内三维自适应高精度定位的核心难题，拟采用现场调研、理论研究、仿真计算、理论分析及现场测试相结合的研究方法，以智能手机WiFi/气压计/IMU多源信号为研究对象，突破室内位置相关的细粒度运动行为精准识别、室内无需先验信息的楼层识别和高度估计、运动行为辅助多条件约束的自适应高精度定位等关键技术，通过场景自适应、运动行为辅助、多条件约束实现智能手机室内亚米级三维定位，有助于完善室内多源混合定位理论和方法，并为位置服务、公共安全、智慧城市等提供重要手段。

Smartphone-based indoor positioning has significant application demands in the fields of location based services, public safety and smart city, such as pedestrian navigation, safety monitoring and early warning, emergency rescue and management, epidemic location tracking, and so on. The complexity of building structure, indoor scene and smartphone usage mode, as well as the diversity of users and signals, make higher requirements on the accuracy and applicability for indoor positioning. Self-adaptive high-precision positioning on smartphone, which is extended to three dimension from two dimension, is both the development trend of current indoor positioning and a big challenge. This project tightly focuses on the core problem of indoor three-dimension self-adaptive high-precision positioning based on smartphone, intending to apply the combination of filed investigation, theoretical research, simulation calculation, theoretical analysis and field tests. Multi-source signals from WiFi/barometer/IMU on smartphone are studied as research object, breaking through key technologies in accurate identification of fine-grained motion behaviors associated with indoor location, floor identification and height estimation without indoor prior information, self-adaptive high-precision positioning with motion behaviors assisted and multiple conditions constrained. The project aims at achieving indoor sub-meter three-dimension positioning based on smartphone by scene adaptation, motion behavior assistance and multi-constrained conditions. It is helpful to improve the theory and method of indoor multi-source hybrid positioning, and provides important means for location based services, public safety, smart city, etc.