Enhancing DF-INS for Accurate Zero-Velocity Detection in ILBS: A Dual Foo

The Dual Foot Inertial Navigation System (DF-INS) shows promise as a practical approach for indoor location-based service (ILBS). Achieving accurate zero-velocity detection is crucial for optimal performance in zero-velocity updating and trajectory calculation. However, conventional techniques rely on fixed thresholds to identify the zero-velocity (stance) phase, which is not suitable for dynamic scenarios and diverse users. This study introduces a dual foot synergistic method to address this issue. Initially, the General Likelihood Ratio Test sequences from both feet are smoothed using a moving average filter. The points of equality within these sequences are then identified as transition points between the stance phase and the swing phase. The experiment was conducted along a closed indoor path, and the results demonstrate that the proposed method outperforms other fixed thresholding methods in terms of zero-velocity detection and DF-INS calculation.