Structure increment-based 6DOF-GPR aircraft aerodynamic modeling method

To address the issues of low efficiency and insufficient dynamic adaptability in traditional aerodynamic modeling, this paper proposes a structural increment-driven six-degree-of-freedom Gaussian Process Regression (6DOF-GPR) hybrid model. Based on the six-degree-of-freedom model, Gaussian Process Regression dynamically compensates for residual nonlinearity. The model utilizes a dual-trigger mechanism combining residual thresholds and variance percentiles to adaptively expand the kernel function. Validation results show that the model achieves RMSE < 0.17 and MAE < 0.4 for axial force, lateral force, and moment during climbing, effectively capturing the dynamic variations in the data.