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Pedestrian dead reckoning (PDR) using inertial and magnetic measurement unit (IMMU) is a current research hotspot that can be used to provide location-based services. The main challenges of the self-contained sensor-based PDR method are mainly sensor errors and orientation estimation errors. In this paper, a novel orientation estimation algorithm and gait phase detection algorithm with strong adaptability are proposed. The variance and magnitude of the angular rate are adopted to detect the gait. The experimental results show that the gait phase detection method can accurately distinguish the swing phase and the stance phase of the foot even under running conditions. By reasonable assumptions, the attitude angles calculated in the swing phase can be calibrated while the attitude angles are in the stance phase. The calibration of velocity not only uses the zero velocity updates method but also makes reasonable assumptions about the bias error of the accelerometer, so that the velocity calculated during the whole swing phase can be calibrated. Experimental results demonstrate that the proposed self-contained IMMU is capable of providing consistent beacon-free PDR in different scenarios, achieving less than 1.2% average distance error and average end-to-end position error.