关键词: 本征正交分解(POD)方法, Fourier级数, BP神经网络算法, 风场预测, 临近空间浮空器

Abstract: The stratospheric wind environment has an important influence on the aerostat design and trajectory control. Taking the wind field data from 2005 to 2010 in Changsha as an example, this paper firstly uses the proper orthogonal decomposition (POD) method to reduce order of the wind field data, and then uses the Fourier series and BP neural network algorithm to predict the stratospheric wind field. The prediction accuracy of the two models is compared and analyzed. Finally, the dynamic model and height control model of the near-space aerostat are established, and the influence of the two wind field prediction models on the trajectory control of the aerostat is analyzed. The research results show that the prediction model based on the BP neural network is more accurate and more reliable than the Fourier prediction model, and it can provide a better reference value for the flight trajectory control of the aerostat.

Key words: proper orthogonal decomposition (POD) method, Fourier series, BP neural network algorithm, wind field prediction, near-space aerostat