Accession Number:

ADA055686

Title:

State Noise Covariance Computation in the Kalman Filter.

Descriptive Note:

Master's thesis,

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OHIO SCHOOL OF ENGINEERING

Personal Author(s):

Report Date:

1977-12-01

Pagination or Media Count:

150.0

Abstract:

This report investigates forms of the state noise covariance matrix in the Kalman Filter. This matrix, denoted Q sub d, incorporates the effects of random errors driving the system dynamics into the filter computations. The Q sub d matrix is derived by integration from the matrix of continuous time driving noise strengths, which normally includes only diagnoal terms. This often leads to use of a diagonal Q sub d matrix with constant terms. However, the derivation shows that Q sub d should have off-diagonal and time varying terms. The study investigates the effects of including such terms in Q sub d. Three alternate forms of Q sub d are derived for a specific inertial navigation system. These, and a standard diagonal form, are tested using a covariance analysis. The results show little difference in performance for the different filters. This is attributed to two primary factors highly accurate external measurements, and the use of integration sub-intervals for covariance propagation.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE