The accuracy of star centroid extraction for star sensor is decreased in the stray light background due to the gray gradients of the star image, a star centroid extraction algorithm based on background removal by least square method is proposed. Firstly, the influence of stray light background on star centroid extraction is analyzed, and the result shows that the systematic error of star centroid extraction is proportion to the background gray gradients. In order to reduce the systematic error, the least square method is used to fit the window edge pixels to obtain the stray light background image, and then the star centroid is extracted through threshold centroid algorithm after removing the stray light background of the star image. The accuracy of star centroid extraction algorithm is simulated through the practical stray light background images. Compared with the traditional threshold centroid algorithm, the systematic error of star centroid extraction can be reduced from 0.021 pixels to 0.002 pixels. The validity of the algorithm is verified by field star observing experiments for star sensor at Xinglong observation station, and the angular distance of the navigation stars is measured and compared with the Hipparcos catalogue. The systematic error of angular distance is reduced from 0.307″ to 0.013″ after the stray light background has been removed by least square method while the operation time is only increased by 6.3%, which can meet the engineering requirements.
A daytime star sensor is a high precision attitude measurement instrument with the ability of detecting stars in the atmosphere during daytime. Different from star sensor applied in space, the performance of daytime star sensor is greatly affected by the strong sky background radiation. The complex and low signal to noise ratio daytime star image increases the difficulties of star recognition. This paper proposes a novel star extraction method for daytime star sensor, mainly focusing on star image preprocessing and fake star removal algorithm. Firstly, an improved morphology Top-Hat filter is provided to suppress the image noise. Then, the detailed process of star extraction is discussed and a pipeline filter is used to reject fake stars. Finally, multi-frame star vectors are calculated and averaged to improve the accuracy. An experiment with daytime star images captured by a self-developed airborne star sensor are analyzed to confirm the validity of the proposed approach, stars can be identified even if there are thin clouds in the sky.
The application of small satellites is a new focus on deep space exploration. Small satellites are easy to launch as secondary payloads, and more suitable for international cooperation. However, small satellites have several major weaknesses for deep space missions, such as the lack of orbit transfer capability and large antenna. This paper presents an innovative concept of small satellite bus based on Evolved Expendable Launch Vehicle (EELV) Secondary Payload Adapter (ESPA). The proposed satellite bus is equipped with orbit control subsystem and a large parabolic antenna for the exploration of Jovian and Saturnian systems. In this paper, the mission requirements, the launch feasibilities and the design parameters of the proposed satellite bus are also discussed.