Angular velocity estimation using characteristics of star trails obtained by star sensor for spacecraft

Abstract

Many studies have been conducted about angular velocity estimation using star sensors, and fairly good performance is achieved when the spacecraft is working at low-dynamic environments. However, when the spacecraft rotates at a large angular velocity, the star image will become blurred, which makes it difficult to identify and recognize star centroids, which, in turn, reduces the accuracy of angular velocity estimation. Therefore, to solve the problem with angular velocity estimation in highly dynamic situations, this research studies a method of angular velocity estimation using blurred star images. The length and ending point coordinates of star trails obtained from these blurred star images are used for a series of processes, which includes the pre-processing of blurred star images, determination of starting and ending points, thinning and selection of star trails, and calculation of trail lengths. Simulations show that the effectiveness of the proposed method in highly dynamic situations and the angular velocity estimation errors in constant and sinusoidal variation are reduced by at least 66% and 62%, respectively, compared with those of the traditional method.

A High-Accuracy Star Centroid Extraction Method Based on Kalman Filter for Multi-Exposure Imaging Star Sensors

“…The star sensor is currently known as the most accurate attitude measurement instrument, and it also has the characteristics of no drift and autonomy [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. Therefore, the star sensor has been widely used in the field of aerospace navigation [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. However, the attitude update rate (AUR) of the traditional star sensor is usually 4–10 Hz, which is too low to accomplish navigation tasks independently.…”