Accession Number:

ADA012013

Title:

Adaptive Sequential Estimation with Unknown Noise Statistics.

Descriptive Note:

Math Lab preprint series no. 7 (Final),

Corporate Author:

AEROSPACE RESEARCH LABS WRIGHT-PATTERSON AFB OHIO

Personal Author(s):

Report Date:

1975-01-01

Pagination or Media Count:

29.0

Abstract:

Sequential algorithms are derived for suboptimal adaptive estimation of the unknown state and observation noise statistics simultaneously with the system state. First- and second-order moments of the noise processes are estimated based on noise samples generated from quantities in the usual Kalman filter algorithm. A limited memory formulation is developed for adaptive correction of the a priori statistics which are intended to compensate for time-varying model errors. The new estimators are applied to an orbit determination problem for a near-earth satellite with significant modeling errors. Results indicate that improved state estimates can be obtained at little computational expense when erroneous a priori noise statistics are adaptively corrected in the filter algorithm.

Subject Categories:

  • Statistics and Probability
  • Spacecraft Trajectories and Reentry

Distribution Statement:

APPROVED FOR PUBLIC RELEASE