Aiming at the fact that the traditional pedestrian dead reckoning (PDR) algorithm can only be used in a single state of normal walking, which is difficult to meet the practical application requirements, an improved PDR algorithm based on adaptive peak detection is proposed. The algorithm divides the pedestrian motion mode into walking and running states, fully considers the relationship between the peak acceleration and the motion state during the pedestrian movement, obtains the peak acceleration under different motion states through experiments, and sets dynamic thresholds to achieve step detection and step size estimation under different states. The improved PDR algorithm is applied to pedestrian positioning: using the pedestrian motion data obtained by the inertial measurement unit (IMU), the improved peak detection method is used to detect the pedestrian steps and identify the pedestrian status, and the adaptive step size estimation formula is used to estimate the step size according to the pedestrian motion status. Finally, the pedestrian position information is obtained by combining the calculated heading. The experimental results show that the improved PDR algorithm has good robustness and high gait recognition rate. Compared with the traditional PDR algorithm, the closedloop error is reduced by 142%, which effectively improves the accuracy of pedestrian positioning results.