Quadratic Filtering Algorithm Based on Covariances Using Correlated Uncertain Observations Coming from Different Sensors
Joint Authors
Caballero-Águila, R.
Linares-Perez, Josefa
Hermoso-Carazo, A.
Source
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-06-30
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
The least-squares quadratic estimation problem of signals from observations coming from multiple sensors is addressed when there is a nonzero probability that each observation does not contain the signal to be estimated.
We assume that, at each sensor, the uncertainty about the signal being present or missing in the observation is modelled by correlated Bernoulli random variables, whose probabilities are not necessarily the same for all the sensors.
A recursive algorithm is derived without requiring the knowledge of the signal state-space model but only the moments (up to the fourth-order ones) of the signal and observation noise, the uncertainty probabilities, and the correlation between the variables modelling the uncertainty.
The estimators require the autocovariance and cross-covariance functions of the signal and their second-order powers in a semidegenerate kernel form.
The recursive quadratic filtering algorithm is derived from a linear estimation algorithm for a suitably defined augmented system.
American Psychological Association (APA)
Caballero-Águila, R.& Hermoso-Carazo, A.& Linares-Perez, Josefa. 2011. Quadratic Filtering Algorithm Based on Covariances Using Correlated Uncertain Observations Coming from Different Sensors. ISRN Applied Mathematics،Vol. 2011, no. 2011, pp.1-18.
https://search.emarefa.net/detail/BIM-449614
Modern Language Association (MLA)
Caballero-Águila, R.…[et al.]. Quadratic Filtering Algorithm Based on Covariances Using Correlated Uncertain Observations Coming from Different Sensors. ISRN Applied Mathematics No. 2011 (2011), pp.1-18.
https://search.emarefa.net/detail/BIM-449614
American Medical Association (AMA)
Caballero-Águila, R.& Hermoso-Carazo, A.& Linares-Perez, Josefa. Quadratic Filtering Algorithm Based on Covariances Using Correlated Uncertain Observations Coming from Different Sensors. ISRN Applied Mathematics. 2011. Vol. 2011, no. 2011, pp.1-18.
https://search.emarefa.net/detail/BIM-449614
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-449614