A Centroid Locating Method for Star Sensor Based on Improved Gaussian Surface Fitting

As a high precision attitude measurement device, star sensors have been widely used in various types of aircraft. Among many factors that affect the attitude measurement accuracy of star sensors, the accuracy of centroid positioning directly affects the accuracy of star map recognition and attitude resolution. In this paper, an improved Gaussian surface fitting method is proposed. Firstly, an improved cross projection method is used to extract star points. Then a simplified Gaussian surface fitting method is adopted to reduce the complexity of the traditional Gaussian surface fitting algorithm. By this algorithm combination, the efficiency and accuracy of the centroid positioning of the stars can be improved at the same time. A series of simulation star graphs are generated by the Gaussian point spread function imaging model, and the centroid positioning accuracy of the traditional centroid locating algorithms and the improved Gaussian surface fitting algorithm are evaluated. Experiments show that the algorithm is simple and easy to implement and the computation amount is small. As a result, the real-time processing of video image information can be achieved, and the positioning accuracy of centroid can be effectively improved.