Estimation of Steady-State Optimal Filter Gain From Nonoptimal Kalman Filter Residuals

[+] Author and Article Information
Chung-Wen Chen

Mars Mission Research Center, North Carolina State University, Raleigh, NC 27695-7910

Jen-Kuang Huang

Department of Mechanical Engineering and Mechanics, Old Dominion University, Norfolk, VA 23529-0247

J. Dyn. Sys., Meas., Control 116(3), 550-553 (Sep 01, 1994) (4 pages) doi:10.1115/1.2899251 History: Received May 24, 1991; Revised June 21, 1993; Online March 17, 2008


This paper proposes a new algorithm to estimate the optimal steady-state Kalman filter gain of a linear, discrete-time, time-invariant stochastic system from nonoptimal Kalman filter residuals. The system matrices are known, but the covariances of the white process and measurement noises are unknown. The algorithm first derives a moving average (MA) model which relates the optimal and nonoptimal residuals. The MA model is then approximated by inverting a long autoregressive (AR) model. From the MA parameters the Kalman filter gain is calculated. The estimated gain in general is suboptimal due to the approximations involved in the method and a finite number of data. However, the numerical example shows that the estimated gain could be near optimal.

Copyright © 1994 by The American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.





Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In