1. Kalman filtering in extended noise environments
- Author
-
Roberto Diversi, Umberto Soverini, Roberto Guidorzi, R. Diversi, R. Guidorzi, and U. Soverini
- Subjects
Optimal estimation ,Monte Carlo method ,KALMAN FILTERING ,Kalman filter ,Variance (accounting) ,Computer Science Applications ,ERRORS-IN-VARIABLES FILTERING ,Noise ,Control and Systems Engineering ,Control theory ,Input estimation ,RECURSIVE FILTERING ,OPTIMAL FILTERING ,Fast Kalman filter ,State (computer science) ,Electrical and Electronic Engineering ,Mathematics - Abstract
This paper introduces an extended environment for Kalman filtering that considers also the presence of additive noise on input observations in order to solve the problem of optimal (minimal variance) estimation of noise-corrupted input and output sequences. This environment includes as subcases both errors-in-variables filtering (optimal estimate of inputs and outputs from noisy observations) and traditional Kalman filtering (optimal stimate of state and output in presence of state and output noise). A Monte Carlo simulation shows that the performance of this extended filtering technique leads to the expected minimal variance estimates.
- Published
- 2005