  Application of two new UKF based estimation techniques with reduced
processing time in re-entry vehicle position and velocity estimation problem
using ground-based range and elevation measurements is presented. The first
method is called the Single Propagation Unscented Kalman Filter (SPUKF) where,
the a postiriori state is propagated only once and then the sampled sigma
points at the next time state are approximated by the first-order Taylor Series
terms. In the second method called the Extrapolated Single Propagation
Unscented Kalman Filter (ESPUKF), the sigma points are approximated to the
second-order Taylor Series terms using the Richardson Extrapolation. The EKF,
SPUKF, ESPUKF and the UKF are utilized in a re-entry vehicle navigation
scenario using range and elevation measurements. The estimation accuracies and
the processing times for different algorithms are compared for the scenario.
The result demonstrates that the UKF provides better accuracy than the EKF but
requires more processing time. The SPUKF accuracy is better than the EKF and
the processing time is significantly less than the UKF. However, the accuracy
of the SPUKF is less than the UKF. The ESPUKF provides estimation accuracy
comparable to the UKF and the processing time is also significantly reduced.
