Open AccessResearch on Flush Air Data Sensing System Based on Kriging Model
Author(s) -
Zhikang Chen,
Guizhou Xu
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2228/1/012045
Subject(s) - kriging , interpolation (computer graphics) , algorithm , artificial neural network , computer science , aerodynamics , artificial intelligence , engineering , machine learning , aerospace engineering , motion (physics)
Compared with traditional air data senening system, flush air data sensing (FADS) system is more accurate, more reliable, and can be used in invisible environment. Algorithm research on FADS was conducted using Kriging model with good real-time and high accuracy. The aerodynamic model of FADS was established while Kriging algorithm was used to calculate flight data with optimized parameter. Mach number, angle of attack, and the aircraft were calculated with simulation and wind tunnel experimental data based on Kriging algorithm. Compared with the neural network algorithm, the inverse distance weight interpolation algorithm, and the SVR fitting algorithm, the results show that the optimized Kriging algorithm performs better.