Navigational star screening method for star sensors

Abstract

The invention relates to a navigational star screening method for star sensors, which includes the following steps: (1) according to the limiting magnitude of a star sensor, the stars of the original star catalogue of the whole celestial sphere are filtered and a star number threshold Nth is determined; (2) the number of the remaining stars of the star sensor in the field of view of the current sky area is set as N; if N is less than or equal to Nth, then all the remaining stars are chosen as navigational stars, and step 3 is executed; and if N is greater than Nth, then the navigational stars in the field of view of the current sky area are segmented and screened by a multi-scale image plane; (3) after the navigational stars in the field of view of the current sky area are screened, the star sensor turns to the next direction to repeat navigational star screening in step 2 until the whole celestial sphere is traversed. The multi-scale image plane segmentation and screening method adopted in the invention can be adapted to the variation in the star numbers of different sky areas to delete the redundant stars of sky areas with high star distribution density and keep all the stars of low-density sky areas, and moreover, the distribution of the screened navigational stars is even.

Description

technical field [0001] The invention belongs to the technical field of celestial navigation, and relates to a method for screening navigation stars for a star sensor. Background technique [0002] The star sensor recognizes the star map, compares the characteristics of the observation star group and the navigation star group, identifies the observation star, determines their coordinates in the body coordinate system and the inertial coordinate system, and then measures the satellite attitude. It is a modern aerospace field. The most accurate satellite attitude measurement instrument. Star map recognition is the core technology of the star sensor. Establishing a navigation star library is an important prerequisite for star map recognition. Reasonable selection of navigation stars can reduce the similarity of navigation star group features, improve star map recognition speed and success rate, and enhance star map recognition. It is of great significance to improve the anti-fa...

AI Technical Summary

Problems solved by technology

In 2000, Li Lihong and others proposed a magnitude weighting method, which assigns different weights to each star according to the magnitude. Stars with low magnitudes have high weights, and stars with high magnitudes have low weights. According to the weights, guide stars are selected. The algorithm is better than the orthogonal grid method, but the algorithm less considers the position of stars, and the uniformity of the distribution of navigation stars needs to be improved

The regression selection algorithm proposed by Zheng Sheng et al. in 2004 is based on the number of observable stars in the field of view, based on the method of support vector machine, to generate a dynamic magnitude threshold, and according to this threshold, observe stars in the field of view in different sky areas to obtain navigation stars , this method can obtain a relatively uniform distribution of navigation stars, but for star sensors with fixed limit magnitudes, the distribution of navigation stars obtained by the regression selection algorithm is still not uniform enough

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