Photometric measurement is an important way to identify the space debris, but the present methods of photometric
measurement have many constraints on star image and need complex image processing. Aiming at the problems, a
statistical learning modeling method for space debris photometric measurement is proposed based on the global
consistency of the star image, and the statistical information of star images is used to eliminate the measurement noises.
First, the known stars on the star image are divided into training stars and testing stars. Then, the training stars are
selected as the least squares fitting parameters to construct the photometric measurement model, and the testing stars are
used to calculate the measurement accuracy of the photometric measurement model. Experimental results show that, the
accuracy of the proposed photometric measurement model is about 0.1 magnitudes.
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