The improvement of star target region extraction algorithm for star centroid

doi:10.11947/j.AGCS.2023.20210674

Abstract

Abstract: The extraction of the target area of star points in star maps is related to the accuracy of the star centroid, which is crucial for celestial navigation. In this paper, an improved algorithm for multi-star target region extraction of a large-field-view star map is proposed to solve the problems of the poor real-time performance of existing boundary search algorithms, the invalidity of boundary search calculation of individual star points, and the inability to recognize and process multiple star points in a single visual frame. The process is as follows: firstly, the visual frame extraction algorithm is used to preliminarily extract the target region. Then, the single-star target region and the target region which may contain multiple stars are screened out by using the diagonal decision algorithm established in this paper. Finally, the boundary search algorithm is used to extract the target region of each star and realize the recognition of the target region of multiple stars. The processing results of measured star maps show that the efficiency of the proposed algorithm is 48% higher than that of the boundary search algorithm. When the visual frame size ranges from 16 to 60 pixels, the accuracy rate of multi-star target region extraction is better than 98%, which can eliminate the star centroid error of nearly 10 pixel caused by the visual frame extraction algorithm, and improve the overall extraction accuracy of star centroid by 3.78 times, reaching 0.038 pixels.

Key words: large field of view star map, star target region, boundary search method, visual frame extraction method

CLC Number:

P222

XU Bin, ZHENG Yong, CHEN Zhanglei, CHEN Bing, CHEN Xiao, LI Chonghui. The improvement of star target region extraction algorithm for star centroid[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(5): 760-768.

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