盲目反卷积算法在高超流场星图复原中的应用

Application of blind deconvolution algorithm in hypersonic flow field star map restoration

近年来高超声速飞行器的研究受到世界各国的重视,具有重大的军事意义,其中导航、制导和控制是高超声速研究的关键技术。鉴于星光导航有着抗干扰能力强、导航精度高、自助式导航等特点,文中主要研究了高超声速飞行器使用星光导航方法的星图复原算法。考虑到高超带来的气动光学效应,在分析高速层流以及湍流流场的基础上,应用增量Wiener滤波器和有限支持域上的盲解卷积复原算法进行退化星图的复原。针对高速飞行器星光导航对复原星图的要求,仿真分析了复原星图的质心偏差及识别特征量变化。仿真结果显示,有限支持域上的盲解卷积复原算法精度较高,且经复原后的星图,能快速被高速飞行器星光导航系统正确识别。

In recent years, the hypersonic aircraft technology is paid more and more attention for its great significance for military application. The guidance, navigation and control technology is one of the key technologies of hypersonic aircraft. And as one of widely used automatic navigation method, which is of such advantages as high navigation accuracy, good anti-interference ability, and auto-navigation ability, the restoration algorithm of star map for hypersonic aircraft was studied in this paper. Considered the aero-optical effects caused by hypersonic flight, the simulation of turbulence-degrade star map was studied, and the increment Wiener filter and the restoration algorithm of iterative blind deconvolution in limitation support region were used for restoration of the turbulence-degraded star map, respectively. The simulation result shows that, the latter method is of higher precision and the restored star map can be identified by the celestial navigation system correctly.