A blurred star image restoration method based on gyroscope data and enhanced sparse model

Author:

Yi JinhuiORCID,Ma Yuebo,Zhu Zifa,Zhu ZijianORCID,Tang Yuping,Zhao Rujin

Abstract

Abstract Star sensors usually have a fixed exposure time to guarantee detection of adequate navigation stars. In a high dynamic environment, star images suffer from degradation due to spacecraft movement, which will severely affects both centroid extraction and attitude accuracy. This paper presents an algorithm for the restoration of motion-blurred star images. The algorithm employs gyroscope assistance and consists of two steps: preprocessing and motion-blurred image restoration. In the preprocessing step, the angular velocity of the gyroscope predicts the motion trajectory, position, and shape of each star point during exposure. This step ensures a good initial estimate of the blur kernel for image restoration. The image restoration step employs an enhanced sparse model inspired by blind deblurring method to solve blur kernel and latent image alternately. Simulations and experiments have verified the effectiveness of the proposed algorithm.

Funder

West Light Foundation of the Chinese Academy of Sciences

Sichuan Outstanding Youth Science and Technology Talent Project

Publisher

IOP Publishing

Subject

Applied Mathematics,Instrumentation,Engineering (miscellaneous)

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