A Study on a High-Precision 3D Position Estimation Technique Using Only an IMU in a GNSS Shadow Zone

초록

Highlights What are the main findings? A novel 3D trajectory estimation mechanism was developed using a single 9-axis IMU that integrates stride-length estimation, heading alignment, and stair-state recognition, enabling accurate and continuous tracking without external references in GNSS-denied environments. Experiments on straight paths, turning routes, and multi-floor stairs showed high accuracy: horizontal error remained below 3% in 100 m, vertical displacement error stayed within 2%, and heading deviation stayed at a sub-radian level, demonstrating excellent stability. What is the implication of the main finding? The proposed mechanism provides a practical and flexible solution for precise agent trajectory estimation in indoor or GNSS-shielded environments, even under resource-constrained conditions. Its accuracy and robustness across mixed gait patterns and vertical transitions support applications such as indoor navigation, emergency response, underground inspection, and wearable/embedded positioning systems.Highlights What are the main findings? A novel 3D trajectory estimation mechanism was developed using a single 9-axis IMU that integrates stride-length estimation, heading alignment, and stair-state recognition, enabling accurate and continuous tracking without external references in GNSS-denied environments. Experiments on straight paths, turning routes, and multi-floor stairs showed high accuracy: horizontal error remained below 3% in 100 m, vertical displacement error stayed within 2%, and heading deviation stayed at a sub-radian level, demonstrating excellent stability. What is the implication of the main finding? The proposed mechanism provides a practical and flexible solution for precise agent trajectory estimation in indoor or GNSS-shielded environments, even under resource-constrained conditions. Its accuracy and robustness across mixed gait patterns and vertical transitions support applications such as indoor navigation, emergency response, underground inspection, and wearable/embedded positioning systems.Abstract In Global Navigation Satellite System (GNSS)-denied environments, reconstructing three dimensional trajectories using only an Inertial Measurement Unit faces challenges such as heading drift, stride error accumulation, and gait recognition uncertainty. This paper proposes a path estimation method with a nine-axis inertial sensor that continuously and accurately estimates an agent's path without external support. The method detects stationary states and halts updates to suppress error propagation. During motion, gait modes including flat walking, stair ascent, and stair descent are classified using vertical acceleration with dynamic thresholds. Vertical displacement is estimated by combining gait pattern and posture angle during stair traversal, while planar displacement is updated through adaptive stride length adjustment based on gait cycle and movement magnitude. Heading is derived from the attitude matrix aligned with magnetic north, enabling projection of displacements onto a unified frame. Experiments show planar errors below three percent for one-hundred-meter paths and vertical errors under two percent in stair environments up to ten stories, with stable heading maintained. Overall, the method achieves reliable gait recognition and continuous three-dimensional trajectory reconstruction with low computational cost, using only a single inertial sensor and no additional devices.

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