Adaptive Kalman Filter Based Aircraft Ground Icing Thickness Prediction

Abstract:

The nonlinear dynamics model is used to describe the change of aircraft icing thickness and icing deformation accelerations is viewed as dynamic noise in this paper. Then, a dynamic prediction model of aircraft icing thickness is established with the theory of adaptive kalman filter. And the adaptive kalman filter method based aircraft icing thickness prediction model is employed to forecast aircraft ground icing thickness and compared with support vector machine, BP neural network prediction method. The result of the instance simulation and analysis indicates that the adaptive kalman filter method based aircraft icing thickness prediction posed in this paper is reliable, simple and rapid, and the model has high prediction precision which can realize real-time tracking and prediction and has definite value of both theory and practice.

• Periodical: Advanced Materials Research (Volumes 562-564)
• Pages: 1660-1667
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.562-564.1660
• Online since: August 2012
• Authors: Zhi Wei Xing, Hui Zhang, Zhun Ren
• Keywords: Adaptive Kalman Filter, Aircraft Icing, Dynamic Noise, Ice Thickness, Prediction Model

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