Optical Navigation Feature Extraction Method for Long-distance Approaching Section of Faint Small Celestial Objects

Abstract

The invention discloses a method for extracting optical navigation features of a faint small celestial body in the long-distance approach section, and belongs to the field of deep space exploration. The invention decomposes trajectory feature extraction into two steps of trajectory refinement and blurred image blind restoration. Firstly, the long-exposure towed star map is denoised and preprocessed; secondly, the trajectory of interest is selected through the selection criteria of the trajectory of interest, and the trajectory of interest is refined by using the pixel-by-pixel OPA algorithm to extract the trajectory skeleton, which is used as a blind restoration The estimated initial value of the blur kernel of the algorithm; finally, construct the cost function of the image restoration algorithm, use the blind restoration algorithm to restore the long-exposure dragging star map to obtain the restored image, and extract the gray-scale optical center of each star point from the restored star map. The invention has the advantages of high extraction precision and fast calculation speed, and is suitable for the feature extraction of the navigation star map of the long-distance approach segment of the faint small astronomical body detector.

Description

technical field [0001] The present invention relates to a method for extracting optical navigation features of dim small celestial bodies in the long-distance approach section, in particular to a star map processing method for small celestial body detection long-distance approach section and long-exposure shooting of dim targets, which can be applied to the long-distance approach section of detectors The autonomous navigation belongs to the field of deep space exploration. Background technique [0002] In the long-distance approach section of the small celestial body detection mission, the probe navigation system needs to determine the attitude by matching the background stars, and determine the orbit by observing the optical center of the target small celestial body. When a small celestial body is used as a navigation star, the navigation target is generally low in magnitude, and it needs to be exposed for a long time before it can be imaged. During the exposure time, the o...

AI Technical Summary

Problems solved by technology

The algorithm of the image matching method is simple, but the image template needs to be pre-stored; the method of grayscale restoration has high autonomy, but the algorithm is more complicated

The present invention estimates the movement of the optical axis by extracting the refined trajectory, which can provide a good initial value for the grayscale restoration problem and thus greatly speed up the convergence of the algorithm. There has been no such attempt in the previous research

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