Paper Info
Title
Multi-stage information fusion identification method for multisensor ARMA signals with white measurement noises
Abstract
For the single channel autoregressive moving average (ARMA) signals with multisensor and white measurement noises, unknown model parameters and unknown noise variances, a multi-stage information identification method is presented. It consists of the recursive instrument variable (RIV) algorithm-based information fusion estimator of the autoregressive (AR) parameters, the correlation method-based information fusion noise variance estimators, and the correlation function-based information fusion moving average (MA) parameter estimator. All information fusion estimators are obtained by taking the average of the local estimators. They have the strong consistency. A simulation example shows its effectiveness.
Year
DOI
Venue
2010
10.1109/ICCA.2010.5524057
ICCA
Keywords
Field
DocType
multistage information fusion identification method,single channel autoregressive moving average,correlation method-based information fusion noise variance estimators,correlation function-based information fusion moving average parameter estimator,multisensor arma signals,white measurement noises,white noise,correlation methods,sensor fusion,recursive instrument variable algorithm-based information fusion estimator,least squares approximation,convergence,noise measurement,moving average,parameter estimation,automation,correlation function,strong consistency,correlation,signal processing,noise
Autoregressive–moving-average model,Autoregressive model,Noise measurement,Pattern recognition,Sensor fusion,White noise,Artificial intelligence,Estimation theory,Moving average,Mathematics,Estimator
Conference
Volume
Issue
ISSN
null
null
1948-3449 E-ISBN : 978-1-4244-5196-8
ISBN
Citations 
PageRank 
978-1-4244-5196-8
1
0.39
References 
Authors
2
3
Name
Order
Citations
PageRank
Yuan Gao113224.12
Huiqin Xu210.39
Zi-li Deng351444.75