Performance analysis of Kalman filter-based clock synchronization in IEEE 1588 networks

2009 ◽  
Author(s):  
G. Giorgi ◽  
C. Narduzzi
Keyword(s):  
Kalman Filter ◽  
Performance Analysis ◽  
Clock Synchronization ◽  
Ieee 1588

scholarly journals Performance Analysis of Computational Intelligence Correction

2021 ◽  
Author(s):  
Nalini Arasavali ◽  
Sasibhushanarao Gottapu
Keyword(s):  
Kalman Filter ◽  
Performance Analysis ◽  
Computational Intelligence ◽  
A Priori ◽  
Covariance Matrices ◽  
System Model ◽  
Process Noise ◽  
Navigation Algorithm ◽  
Modified Kalman Filter ◽  
Measurement Noises

Abstract Kalman filter (KF) is a widely used navigation algorithm, especially for precise positioning applications. However, the exact filter parameters must be defined a priori to use standard Kalman filters for coping with low error values. But for the dynamic system model, the covariance of process noise is a priori entirely undefined, which results in difficulties and challenges in the implementation of the conventional Kalman filter. Kalman Filter with recursive covariance estimation applied to solve those complicated functional issues, which can also be used in many other applications involving Kalaman filtering technology, a modified Kalman filter called MKF-RCE. While this is a better approach, KF with SAR tuned covariance has been proposed to resolve the problem of estimation for the dynamic model. The data collected at (x: 706970.9093 m, y: 6035941.0226 m, z: 1930009.5821 m) used to illustrate the performance analysis of KF with recursive covariance and KF with computational intelligence correction by means of SAR (Search and Rescue) tuned covariance, when the covariance matrices of process and measurement noises are completely unknown in advance.

Performance Analysis of the Kalman Filter With Mismatched Noise Covariances

2016 ◽  
Vol 61 (12) ◽  
pp. 4014-4019 ◽  
Author(s):  
Quanbo Ge ◽  
Teng Shao ◽  
Zhansheng Duan ◽  
Chenglin Wen
Keyword(s):  
Kalman Filter ◽  
Performance Analysis
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