3D-IMB-APDR: Inertial-Geomagnetic-Barometric-Based Adaptive Infrastructure-Free 3D Pedestrian Dead Reckoning Method

With the rapid development of underground spaces and demand for infrastructure-independent autonomous positioning in post-disaster rescue, Pedestrian Dead Reckoning (PDR) has become a key research focus. However, traditional PDR suffers from cumulative heading drift, inadequate 3D positioning performance, and poor anti-magnetic interference capabilities, failing to meet the high-precision positioning requirements of rescuers in underground and multistory buildings. To address these issues, this paper proposes an adaptive 3D-PDR method fusing inertial, geomagnetic, and barometric (3D-IMB-APDR). Sensor data are optimized via FFT dominant frequency extraction and Butterworth zero-phase filtering, with magnetic interference compensated by geomagnetic ellipse fitting. A segmental heading correction with a multi-criteria dynamic geomagnetic reliability model suppresses heading drift. A barometer-based coarse estimation and inertial fine correction architecture is adopted, where a lightweight CNN-BiLSTM network extracts inertial features for step height, and AEKF fuses multi-source data to achieve accurate vertical height estimation and precise 3D positioning. Validated in sports fields, underground parking garages, and staircases, the method outperforms four comparative methods, reducing positional RMSE by 65.77–98.23%, with endpoint errors of 1.40 m, 2.56 m, and 0.32 m, respectively. Relying solely on chest-worn sensors, it provides a reliable 3D autonomous positioning solution for rescuers in post-disaster rescue and underground engineering.