6 February 2018 Spacecraft angular velocity estimation algorithm for star tracker based on optical flow techniques
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An integrated navigation system often uses the traditional gyro and star tracker for high precision navigation with the shortcomings of large volume, heavy weight and high-cost. With the development of autonomous navigation for deep space and small spacecraft, star tracker has been gradually used for attitude calculation and angular velocity measurement directly. At the same time, with the dynamic imaging requirements of remote sensing satellites and other imaging satellites, how to measure the angular velocity in the dynamic situation to improve the accuracy of the star tracker is the hotspot of future research. We propose the approach to measure angular rate with a nongyro and improve the dynamic performance of the star tracker. First, the star extraction algorithm based on morphology is used to extract the star region, and the stars in the two images are matched according to the method of angular distance voting. The calculation of the displacement of the star image is measured by the improved optical flow method. Finally, the triaxial angular velocity of the star tracker is calculated by the star vector using the least squares method. The method has the advantages of fast matching speed, strong antinoise ability, and good dynamic performance. The triaxial angular velocity of star tracker can be obtained accurately with these methods. So, the star tracker can achieve better tracking performance and dynamic attitude positioning accuracy to lay a good foundation for the wide application of various satellites and complex space missions.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Yujie Tang, Jian Li, Gangyi Wang, "Spacecraft angular velocity estimation algorithm for star tracker based on optical flow techniques," Optical Engineering 57(2), 023101 (6 February 2018). https://doi.org/10.1117/1.OE.57.2.023101 . Submission: Received: 27 September 2017; Accepted: 10 January 2018
Received: 27 September 2017; Accepted: 10 January 2018; Published: 6 February 2018

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