An algorithm to correct the degradation of interference spectral imaging caused by motion errors

In the spectral imaging process of interference imaging spectrometer, the impact caused by motion errors of satellite platform is not only the degradation of spatial resolution but also the aliasing and distortion of spectral information. The degradation function is modeled though analyzing the degradation mechanism of spectral imaging. And a correction algorithm based on interference sequences is proposed to solve this problem. In this algorithm, the interference sequences is regarded as an integer and the degradation model is thought to be three-dimensional, including two spatial dimensions and one spectral dimension. And the degraded interference sequences are the convolution of the original sequences and the degradation function. According to the vibration data measured by POS on the satellite, the degradation function can be obtained. Then the corrected interference sequences can be got by de-convolution of the degraded sequences and the degradation function though Hopfield neural network based on continuous variation of states. And by reconstructing of the corrected sequences, the corrected images and spectrums can be got finally. The simulated results show that this algorithm can correct the degradation of images and the distortion of spectrums caused by motion errors of satellite's attitudes effectively.