Small body gravitational field modeling method based on gaussian process regression
A technology of Gaussian process regression and modeling method, which is applied in the field of modeling the gravitational field of small celestial bodies, and can solve problems such as inability to obtain accurate solutions, reduction of calculation amount, and complex calculation process.
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[0071] In order to better illustrate the purpose and advantages of the present invention, the content of the invention will be further described below in conjunction with the accompanying drawings and examples.
[0072] This example calculates the gravitational acceleration g of 10,000 inspection points within 20km of the small celestial body 433Eros from the center of mass. The density of 433Eros is 2.67×10 12 kg / km 3 , the small celestial gravitational constant is 0.4401×10 -3 km 3 / s 2 . In order to prove the applicability of the method, the inspection points are randomly obtained, and the modeling results are compared with the results and time calculated by the polyhedron method.
[0073] Such as figure 1 As shown, the small celestial body gravitational field modeling method based on Gaussian process regression GPR disclosed in this embodiment, the specific implementation method is as follows:
[0074] Step 1: Obtain the training set of gravitational field data by po...
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