1887
Volume 25 Number 4
  • E-ISSN: 1365-2478

Abstract

A

Ott and Meder's prediction error filter can be rederived so that it correctly handles input noise vectors which are of smaller dimension than the state vector. The poor performance obtained by Ott and Meder for their example can be explained by means of the error covariance matrix for the prediction error filter.

Loading

Article metrics loading...

/content/journals/10.1111/j.1365-2478.1977.tb01197.x
2006-04-27
2020-07-07
Loading full text...

Full text loading...

References

  1. Kailath, T., 1968, An Innovations Approach to Least‐Squares Estimation Part I: Linear Filtering in Additive White Noise, IEEE Transactions on Automatic Control, AC‐13, 646–655.
    [Google Scholar]
  2. Meditch, J. S., 1969, Stochastic Optimal Linear Estimation and Control, McGraw‐Hill Book Co., New York .
    [Google Scholar]
  3. Mendel, J. M.1977, “Single‐Channel White Noise Estimators for Deconvolution,” Geophysics.
  4. Ott, N. and Meder, H. G., 1972, “The Kalman Filter as a Prediction Error Filter,” Geophysical Prospecting20, 549–560.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/j.1365-2478.1977.tb01197.x
Loading
  • Article Type: Research Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error