An ameliorated GWO-KNN method for localization of hypervelocity impact on the complex spacecraft structure

The increasing number of space debris poses a significant impact threat to spacecraft, especially the large-scale Space Station with complex structural features. Thus, real-time in-situ localization of the hypervelocity impact events is crucial for ensuring the on-orbit safety of spacecraft. Traditional damage localization methods (empirical or signal integrity-based) are inadequate for hypervelocity impact (HVI) on complex spacecraft, due to wave propagation complexities (anisotropy, signal distortion, and mode conversion) introduced by structural elements like stiffeners and perforations. To address this, a grey wolf optimizer (GWO)-K nearest neighbor (KNN) localization method is proposed, including: (i) a hierarchical localization approach is developed, combining improved KNN identification with weighted centroid refinement; (ii) the algorithm performance is optimized through regularized KNN weighting and GWO-trained parameters for robust TDOA-to-location mapping; and (iii) comprehensive experimental validation is conducted, including low-velocity impact testing for TDOA library generation, spatial error analysis, and HVI verification. Comparative analysis demonstrates the proposed algorithm’s superior robustness in localization accuracy over conventional KNN-weighted centroid methods, particularly in overcoming material-dependent wave velocity variations. This advancement enables reliable impact localization in complex spacecraft structures.