Low-orbit satellite precision orbit determination strategy supported by machine learning
A machine learning and precise orbit determination technology, applied in machine learning, artificial satellites, instruments, etc., can solve the problems of high conditions and long periods of observation.
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[0059] A set of common simplified policy combinations is used as the policy space and labeled separately:
[0060] (11) Simultaneous estimation of atmospheric drag and light pressure,
[0061] (10) Estimates of atmospheric drag only,
[0062] (00) Atmospheric resistance and light pressure are not estimated.
[0063] Considering the characteristics of the machine learning design samples and the available actual samples, a number of civil and commercial low-orbit satellites with orbital heights ranging from 400km to 1000km were selected as training samples, and the S-band signals of the sample satellites were continuously observed for several months. (up to one year). The data of 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, and 5.0 days are selected for precise orbit determination every month, and no orbital maneuvers are guaranteed during this period. The data set has a total of 709 pieces of data, including 358 pieces with the label 00, 289 pieces with the label 10, and 62 pieces with the...
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