DocumentCode :
567689
Title :
Online EM algorithm for joint state and mixture measurement noise estimation
Author :
Özkan, Emre ; Fritsche, Carsten ; Gustafsson, Fredrik
Author_Institution :
Dept. of Electr. Eng., Linkoping Univ., Linkoping, Sweden
fYear :
2012
fDate :
9-12 July 2012
Firstpage :
1935
Lastpage :
1940
Abstract :
In this study, we aim to estimate the unknown multi-modal measurement noise distribution of nonlinear state space models. The unknown noise distribution is modeled as a mixture of exponential family of distributions. We use the Expectation-Maximization (EM) method in order to jointly estimate the unknown parameters as well as the states. The online version of the EM algorithm is implemented by using particle filtering techniques. The resulting algorithm is a noise adaptive particle filter which is applicable to many sensor models having multi-modal noise distributions with unknown parameters.
Keywords :
adaptive signal processing; estimation theory; noise; optimisation; particle filtering (numerical methods); expectation-maximization method; joint state; mixture measurement; multimodal measurement; noise adaptive particle filter; noise estimation; nonlinear state space models; online EM algorithm; particle filtering techniques; unknown noise distribution; Approximation methods; Equations; Hidden Markov models; Maximum likelihood estimation; Noise; Noise measurement; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2012 15th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4673-0417-7
Electronic_ISBN :
978-0-9824438-4-2
Type :
conf
Filename :
6290537
Link To Document :
بازگشت