UD filtering and smoothing applied to orbit determination

Details UD filtering and smoothing applied to orbit determination UD filtering and smoothing applied to orbit determination

Aug 1989

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1989stin...9022501k&link_type=abstract

Presented at the International Symposium on Space Dynamics, Toulouse, France, 6-10 Nov. 1989

Computer Science

Performance

Adaptive Filters, Digital Simulation, Factorization, Kalman Filters, Orbit Calculation, Orbits, Postflight Analysis, Smoothing, Trajectories, Covariance, Degradation, Divergence, Estimates, Estimating, Noise Intensity, Real Time Operation, Tracking Stations

Scientific paper

The performance is described of filtering and smoothing techniques applied to orbit determination of earth satellites. A (forward pass) Kalman filter along with an adaptive procedure for estimating the dynamic noise level which prevents the divergence of estimates due to inaccurate modelling of the orbital motion is implemented in the UD factorization form. The backward smoother is a numerically efficient version of the Rauch-Tung-Striebel (RTS) smoother. This smoother, developed in the UD form, has proven to be economical, compact and competitive for computer implementation. Digital simulations are performed for 2 situations of orbit determination: short arc orbit determination with favorably tracking geometry; and long arc orbit determination with existing tracking stations. Tests containing many levels of modelling degradation are carried out. The forward pass adaptive UD filter behaves so as to deal with these modelling nuisances and does not allow the divergence phenomenon to occur. In no real time operations, the backward UD smoother is used to improve the accuracy of the estimates and of the covariances resulting from the filtering phase. The results show, in the main, that the UD smoother can enhance the accuracy of the forward pass filter, sometimes by an order of magnitude. For post-flight analysis, the UD smoother is a useful tool when one aims at reconstituting the entire trajectory of the orbital motion covered by the tracking data.

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