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Online EM algorithm for joint state and mixture measurement noise estimation
Date
2012-07-09
Author
Zhao, Yuxin
Yin, Feng
Gunnarsson, Fredrik
Amirijoo, Mehdi
Özkan, Emre
Gustafsson, Fredrik
Metadata
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In this study, we aim to estimate the unknown multimodal 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 ExpectationMaximization (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 multimodal noise distributions with unknown parameters.
Subject Keywords
Algorithms
,
Information fusion
,
Monte Carlo methods
,
Sensors
,
Signal filtering and prediction
,
State space methods
URI
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6290537
https://hdl.handle.net/11511/78046
Conference Name
15th International Conference on Information Fusion, FUSION 2012; (7 September 2012 through 12 September 2012)
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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Y. Zhao, F. Yin, F. Gunnarsson, M. Amirijoo, E. Özkan, and F. Gustafsson, “Online EM algorithm for joint state and mixture measurement noise estimation,” presented at the 15th International Conference on Information Fusion, FUSION 2012; (7 September 2012 through 12 September 2012), Singapore, 2012, Accessed: 00, 2021. [Online]. Available: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6290537.