.png){kind=icon}
.png){kind=icon}
Return
Measurement Difference Method: A Universal Tool for Noise Identification
.png){kind=icon}
PRE
AI
DOI：10.1109/TAC.2022.3160679.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This article deals with noise identification of a system described by the linear time-varying state-space model using correlation methods. In particular, the stress is laid on the measurement difference method (MDM) as a universal tool allowing estimation of moments and parameters of the state and measurement noises. The recent results are summarized in a common framework and the full (and weighted) MDM implementation is developed. This implementation provides unbiased and weakly consistent estimate of an arbitrary raw or central moment of the state and measurement noises. The performance of the method is shown in a numerical study.
Keywords:
Covariance matrices
Noise measurement
Correlation
Time measurement
State-space methods
Probability density function
Computational modeling
Correlation methods
identification
linear systems
Index Terms
noise moments
noise parameters
state-space models
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W