Application of extended Kalman filter to satellite precise prediction

Statistics – Computation

Scientific paper

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Kalman Filters, Laser Range Finders, Position Errors, Satellite Tracking, Site Data Processors, Tracking Stations, Aerodynamic Drag, Dynamic Models, Geocentric Coordinates, Orbit Perturbation, Radiation Pressure, Real Time Operation, Signal Processing

Scientific paper

An orbit-improving Kalman filter is suggested that permits precise prediction of satellite position by real-time processing of a few passes of laser-ranging observation data from only one tracking station. The dynamical model includes the effects of the earth's shape, atmospheric drag, solar radiation pressure, and lunar and solar perturbations. For the computation, the earth's gravitational potential was developed up to the 11th degree and 11th order for all zonal, sectorial, and tesseral harmonic terms. An exponential model was adopted for the distribution of atmospheric density, the earth's shadow was assumed to be cylindrical, and rotating Kepler's elliptical orbits were adopted in computing the geocentric coordinates of the moon and sun. To estimate the satellite state, the extended sequential estimation algorithm was applied, and the numerical method was used to integrate the state vector and the error covariance matrix. Two tests using simulated and real laser ranging data were done, and the results are presented.

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