An online fault detection method for UAV navigation based on spatial motion coordinates*
Xinyi Wan, Chuanyang Li, Zeming Zhang, Changhua Hu, Mingzhe Leng · 2025
To address the challenging issue of online fault discrimination in unmanned aerial vehicle (UAV) navigation systems, this paper introduces an innovative fault detection method that leverages spatial motion coordinates. This approach performs online synchronization, linear interpolation and smoothing on the spatial motion coordinate position data. By calculating the position, velocity and acceleration of the given data and selecting the fault discrimination thresholds adaptively through a grid search algorithm, the fault discrimination are fast realized. Then, the simulation date randomly generated is employed to validate the procedure. It turns out that the proposed method discriminate effectively anomalies for the UAV navigation systems in real time based on a single spatial motion coordinate data, such as position, velocity, or acceleration information, which improves the accuracy and stability of the system of the interest. The innovative method for fault discrimination demonstrates high sensitivity and robustness, providing theoretical and technical support for the safety of UAV flight