INS constraint algorithm based on adaptive zerovelocity update algorithm with heading angle error correction

To improve the positioning accuracy of a pedestrian inertial navigation system (INS), an INS constraint algorithm based on an adaptive zero-velocity update algorithm (ZUPT) and heading angle error correction was proposed. First, the threshold of zero-velocity detection based on the generalised likelihood ratio and eigenvalue of the test statistic are used to establish an equation and adaptive adjustment of the threshold of zero-velocity detection. Subsequently, a linear regression model was established based on the solution position of the INS. Combining the heading difference between the main heading and solved heading, the observation vector and observation matrix are constructed according to the pedestrian movement type to correct the INS error. Ultimately, the experimental validation confirmed that when pedestrians move in a complex route with variable velocity, compared with the zero-velocity detection algorithm with a fixed threshold and the main course correction algorithm, the proposed algorithm is closer to the real trajectory, and the average closed-loop error is reduced from $3.31 \% \mathrm{D}$ to $1.45 \%$ D, which effectively improves the positioning accuracy of the INS and has good engineering application value.