南京航空航天大学学报（自然科学版）2026，Vol.58Issue(3)：682-695,14.DOI:10.16356/j.2097-6771.2026.03.021
基于MFP-TCN-iTransformer模型QAR数据驱动的飞机俯仰角预测方法
A QAR Data-Driven Aircraft Pitch Angle Prediction Method Based on the MFP-TCN-iTransformer Model
摘要
Abstract
To achieve precise prediction of pitch angles,this paper proposes a TCN-iTransformer model,named MFP-TCN-iTransformer,that integrates multi-flight phase(MFP)encoding.This method constructs a joint prediction architecture:The iTransformer module extracts global temporal features from quick access recorder(QAR)data and captures cross-variable dependencies,while the temporal convolutional network(TCN)module models multi-scale temporal dependencies of the pitch angle through dilated convolution.Additionally,MFP encoding is introduced,dividing the flight process into five phases to distinguish the data characteristics of different stages.Finally,a feature fusion mechanism is designed to combine discrete phase information with continuous QAR data,enhancing the model's adaptability to phase characteristics.Experiments based on 264 352 pieces of QAR data show that the proposed model achieves an average improvement of 19.16%and 22.05%in mean absolute error(MAE)and root mean square error(RMSE),respectively,compared to other benchmark models.Systematic ablation studies subsequently verify the effectiveness of each core component and confirm that refined flight phase encoding brings stable performance improvements.The results indicate that the model can achieve high-precision pitch angle prediction,which has practical value for enhancing flight safety.关键词
俯仰角预测/MFP-TCN-iTransformer模型/快速存取记录器/多飞行阶段编码/飞行安全Key words
pitch angle prediction/MFP-TCN-iTransformer model/quick access recorder(QAR)/multi-flight phase(MFP)encoding/flight safety分类
信息技术与安全科学引用本文复制引用
王兴隆,宋子凯,薛鹏..基于MFP-TCN-iTransformer模型QAR数据驱动的飞机俯仰角预测方法[J].南京航空航天大学学报（自然科学版）,2026,58(3):682-695,14.基金项目
国家重点研发计划(2023YFB4302905). （2023YFB4302905）
