An Improved Kalman Filter for Satellite Orbit Predictions
Abstract
The nonlinear problem of tracking and predicting where a satellite will be over some time can be difficult with the recognition of modeling error and ground site radar tracking errors. For this reason it is important to have an accurate modeling program with the fidelity to correct for any errors in orbital motion and predict the most accurate positioning at some future time. The Extended Kalman Filter is one such program that can accurately determine position over time given estimate ranges for sources of error. However, the Extended Kalman Filter contains many linear approximations that allow its prediction and correction methods to work. This paper will discuss the effects of replacing the linearizing approaches made in the orbital model part of the program with numerical small-step approaches. The overall errors during prediction will be compared for an analysis of the corrective ability of the filter. Additionally a final prediction at a later date and another location will serve as an indicator to the usefulness of the prediction capabilities over time.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2004
- Accession Number
- ADA431057
Entities
People
- Luke Sauter
- Paul Vergez
- Scott Dahlke
Organizations
- United States Air Force Academy