Focusing on the repetitiveness of geomagnetic fingerprints and accumulated error in Pedestrian Dead Reckoning (PDR), a fusion indoor localization method was proposed by using multiple sensors of smartphone. Firstly, WiFi and RANdom SAmple Consensus (RANSAC) algorithm were used to find initial positions of users. Then the step length was calculated by using the accelerometer of smartphone, and the conclusion of turn was given by gyroscope. Finally, the localization of PDR was corrected by means of geomagnetic field using map-constrained adaptive Particle Filter (PF), which is a high precision indoor localization method. The simulation results show that the proposed method can effectively overcome the accumulated error of the PDR and the repetitiveness of geomagnetic values, improve the positioning accuracy and reduce the energy consumption.