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In order to improve the accuracy of indoor positioning, the step detection, stride length estimation and heading estimation of pedestrian dead reckoning are improved. Firstly, by combining the self-correlation analysis algorithm and the adaptive peak detection method, a new detection algorithm is proposed. Secondly, based on Scarlett model, a new stride length measurement model is proposed that takes the stride length of the previous step into consideration. Thirdly, based on the algorithm of the orientation, the main navigation direction is set, and the Kalman filter is used for reduce the heading estimation error of walking in a straight line. Finally, the experiments verified that the improved method improves the accuracy of step detection and stride length estimation and reduces the heading angle error and achieves the better result in the indoor positioning.