Data depth weight kernel estimator of satellite orbit determination model error

Astronomy and Astrophysics – Astronomy

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Celestial Mechanics: Orbit Determination, Methods: Numerical

Scientific paper

It is objective that the satellite dynamic model exits error, and the dynamic model error will
be transmitted to satellite orbit determination model with connotative format, commingled together with measurement system error and stochastic error, and form the new mixing model error which will badly pollute the precision of orbit determination. Orbit determination model with dynamic model error was deducted in detaile, while the parametric model for exact dynamic model was produced as well as non parametric model for mixing model error. Thus partially linear orbit determination model was proposed along with its solve method to estimate model error with two stage method and kernel function method, and the estimated model error will be compensated to improve the precision of orbit determination. Because of the non steadiness of the kernel function, a data depth weight kernel estimator for model error was produced based on the data depth theory so as to restrain the singular data. Finally, simulation experiment of SBSS was processed, the results showed that the kernel function can effectively estimate the model error, but a important parameter is the window of kernel. The precision of orbit determination can be improved by compensate the model error and the data depth weight kernel estimator can effectively restrain the singular data of observation error.

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