Model error estimation by ideal state processing in linear Kalman filter

1992 ◽  
Vol 15 (3) ◽  
pp. 775-777 ◽  
Author(s):  
S. K. Pillai ◽  
S. S. Balakrishnan ◽  
V. Seshagiri Rao ◽  
N. Narasaiah
Keyword(s):  
Kalman Filter ◽  
Error Estimation ◽  
Model Error ◽  
Ideal State ◽  
State Processing

TREATMENT OF THE ERROR DUE TO UNRESOLVED SCALES IN SEQUENTIAL DATA ASSIMILATION

2011 ◽  
Vol 21 (12) ◽  
pp. 3619-3626 ◽  
Author(s):  
ALBERTO CARRASSI ◽  
STÉPHANE VANNITSEM
Keyword(s):  
Dynamical System ◽  
Kalman Filter ◽  
Data Assimilation ◽  
Large Scale ◽  
Model Error ◽  
Environmental Modeling ◽  
Sequential Data ◽  
Chaotic Dynamical System ◽  
Error Covariance ◽  
Sequential Data Assimilation

In this paper, a method to account for model error due to unresolved scales in sequential data assimilation, is proposed. An equation for the model error covariance required in the extended Kalman filter update is derived along with an approximation suitable for application with large scale dynamics typical in environmental modeling. This approach is tested in the context of a low order chaotic dynamical system. The results show that the filter skill is significantly improved by implementing the proposed scheme for the treatment of the unresolved scales.

An Adaptive Phase Tracking Scheme of OFDM Wireless Communication System

2013 ◽  
Vol 336-338 ◽  
pp. 1798-1803
Author(s):  
Qian Du ◽  
Wen Wu Xie
Keyword(s):  
Kalman Filter ◽  
Wireless Communication ◽  
Channel Estimation ◽  
Error Estimation ◽  
Communication System ◽  
Phase Error ◽  
Basic Structure ◽  
Adaptive Kalman Filter ◽  
Phase Tracking ◽  
New Phase

This paper proposes a new phase tracking algorithm for the 802.11a system. Since this system illuminates the basic structure of 802.11a system, and introduces the OFDM frame generation principle based the transmitter, phase error estimation and channel estimation. On the basis of this, this paper presents a phase tracking scheme based on adaptive Kalman filter, and then simulates the process based on 802.11a system. The result indicates that the BER has been improved because of this adaptive phase tracking scheme.

Model Error Estimation for the Simplified PN Radiation Transport Equations

2020 ◽  
Vol 194 (10) ◽  
pp. 903-926
Author(s):  
Yunhuang Zhang ◽  
Jean C. Ragusa ◽  
Jim E. Morel
Keyword(s):  
Error Estimation ◽  
Radiation Transport ◽  
Model Error ◽  
Transport Equations
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