Kalman Filter Riccati Equation for the Prediction, Estimation, and Smoothing Error Covariance Matrices

  • Assimakis N
  • Adam M
N/ACitations
Citations of this article
38Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The classical Riccati equation for the prediction error covariance arises in linear estimation and is derived by the discrete time Kalman filter equations. New Riccati equations for the estimation error covariance as well as for the smoothing error covariance are presented. These equations have the same structure as the classical Riccati equation. The three equations are computationally equivalent. It is pointed out that the new equations can be solved via the solution algorithms for the classical Riccati equation using other well-defined parameters instead of the original Kalman filter parameters.

Cite

CITATION STYLE

APA

Assimakis, N., & Adam, M. (2013). Kalman Filter Riccati Equation for the Prediction, Estimation, and Smoothing Error Covariance Matrices. ISRN Computational Mathematics, 2013, 1–7. https://doi.org/10.1155/2013/249594

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free