Star extraction method for star sensor at a high angular rate
When a star sensor slews at a high angular rate, the stars in the sensed image are smeared out over many pixels, which results in a decreasing signal-to-noise ratio (SNR). Therefore, the faint stars are not capable of being detected, and the centroidal precision of the bright stars decrease when using traditional image threshold segmentation algorithm and centroid method. In this paper, we propose a method to obtain accurate star location for star sensor at a high angular rate. We first utilize Laplacian to segment the star image, and then each pixel is marked after it is compared with the neighbouring one. Finally, the centroids of stars are calculated by using target pixels, and the centroiding errors are compensated. The experiment results illustrate that the proposed technique can extract more stars than other traditional methods under the condition of high angular rate, and also can improve the locating precision of star effectively.
Improved approach to star extraction from star image
Based on the vector technique,an improved approach to star extraction from star image is proposed,which comprised of the improved SUSAN algorithm and the limited pixel labeling technique.The simulation results show that the precision of the proposed algorithm is much higher than that of the vector technique and it has strong abilities of anti-noise and eliminating faint star.
A novel geometric structure-based autonomous star pattern identification algorithm
A novel geometric structure-based autonomous star pattern identification algorithm is presented. The matching procedure of the triplet between measured stars in the spacecraft body frame and corresponding reference stars known in the inertial frame is transformed partially into a geometric structure feature value matching problem by preprocessing the measurement error ahead of the matching procedure, since the star triplet removed the measurement error can be changed into integer triplet. The number of feature needed in the star pattern identification procedure are reduced by the introduction of the geometric structure feature. Even if the error or redundant matches exist in the triangle identification procedure, the correct identification rate is effectively improved by the combination of multi-triplets. Compared to the traditional triplet approach, the geometric structure-based star pattern recognition algorithm has a couple of advantages, including the smaller database of guide star pattern, higher rate of correct star pattern recognition, lower mismatches probability, and better real-time adaptability and robustness.