To address the problem that roller coasters are difficult to locate, this article proposes a roller coaster localization method based on time series alignment. The method firstly uses the dynamic time warping (DTW) to align the inertial measurement unit ( IMU) measured data with the simulated data to obtain the estimated position of roller coaster. Subsequently, the error state Kalman filter (ESKF) is used to update the IMU-based prediction by using the DTW estimation as observation. To improve the accuracy of the estimation, the segment recombination dynamic time warping (SRDTW) algorithm is proposed to solve the distortion problem of DTW. The localization experiments of a roller coaster are conducted using the method in this article. The results show that time series alignment using Z-directional acceleration and pitch angle can provide more accurate position estimation, and the average error after ESKF filtering can reach 0. 24 m, which is 45. 6% lower than average error of estimation alone.